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+# KV Cache Explainer Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** Add a `/kv-cache` route to the transformer-explainer repo that visualizes the KV cache mechanism — prefill shows the existing N×N attention matrix, then decode steps show a growing KV cache table (K in red, V in green) and a 1×N attention strip.
+
+**Architecture:** New SvelteKit route at `src/routes/kv-cache/` that copies the root page structure. `AttentionMatrix.svelte` gets an `isDecoding` reactive binding from a new `src/store/kvcache.ts` store that switches its rendering from N×N to 1×N + KVCacheTable. Pre-computed example data (5 prompts × ~5 decode steps each) is generated offline by a Python script and stored as JS modules.
+
+**Tech Stack:** SvelteKit 2, Svelte 5, TypeScript, GSAP 3, D3 7, Tailwind CSS 3, Python 3 + HuggingFace `transformers` (offline data generation only)
+
+---
+
+## File Map
+
+| File | Action | Responsibility |
+|------|--------|----------------|
+| `scripts/generate_kv_examples.py` | Create | Offline: runs GPT-2, extracts KV cache + attention scores per decode step |
+| `src/constants/examples/kv/ex0.js` – `ex4.js` | Create | Decode step data only (prefill reuses existing `ex0`–`ex4` which have full ONNX outputs) |
+| `src/constants/examples/kv/index.js` | Create | Re-exports all 5 KV decode examples |
+| `src/store/kvcache.ts` | Create | `decodeStep`, `kvCache`, `isDecoding`, `currentDecodeData`, `promptTokenCount` stores |
+| `src/components/KVCacheTable.svelte` | Create | Animated growing table: token × K vector (red) × V vector (green) |
+| `src/components/AttentionMatrix.svelte` | Modify | Import `isDecoding`; when true render 1×N strip + KVCacheTable instead of N×N |
+| `src/routes/kv-cache/+page.ts` | Create | `export const prerender = true` |
+| `src/routes/kv-cache/+page.svelte` | Create | Root page copy + decode step controls, KV example data loading |
+| `svelte.config.js` | Modify | Add `/kv-cache` to prerender entries |
+
+---
+
+## Task 1: Python data generation script
+
+**Files:**
+- Create: `scripts/generate_kv_examples.py`
+
+This runs offline (not part of the web app). It uses HuggingFace `transformers` to run GPT-2 on each of the 5 prompts, extracts KV cache and attention scores at each decode step, and writes JS module files.
+
+- [ ] **Step 1: Install dependencies (run once)**
+
+```bash
+pip install torch transformers
+```
+
+- [ ] **Step 2: Create the script**
+
+Create `scripts/generate_kv_examples.py`:
+
+```python
+"""
+Generates KV cache example data for the kv-cache-explainer.
+Run: python scripts/generate_kv_examples.py
+Output: src/constants/examples/kv/ex{0..4}.js
+"""
+
+import torch
+import json
+import os
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+DECODE_STEPS = 5
+OUTPUT_DIR = "src/constants/examples/kv"
+
+PROMPTS = [
+    "Data visualization empowers users to",
+    "Artificial Intelligence is transforming the",
+    "As the spaceship was approaching the",
+    "On the deserted planet they discovered a",
+    "IEEE VIS conference highlights the",
+]
+
+def extract_head_vectors(past_key_values, head_idx=0):
+    """
+    Extract K and V vectors for all tokens for a specific head.
+    past_key_values: tuple of (key, value) per layer
+    Returns: list of {token_idx: {keys: [64], values: [64]}} per layer (we use layer 0 for display)
+    """
+    # Use layer 0, head head_idx
+    # key shape: [batch=1, num_heads=12, seq_len, head_dim=64]
+    keys_all_heads = past_key_values[0][0][0]   # [12, seq_len, 64]
+    values_all_heads = past_key_values[0][1][0] # [12, seq_len, 64]
+
+    # Return all heads for head selector support
+    # Shape: [12 heads, seq_len, 64]
+    return {
+        "keys": keys_all_heads.tolist(),    # [12, seq_len, 64]
+        "values": values_all_heads.tolist() # [12, seq_len, 64]
+    }
+
+def extract_attention_scores(attentions, seq_len):
+    """
+    Extract 1xN attention scores for the last token from all layers and heads.
+    attentions: tuple of [batch=1, num_heads=12, query_len, key_len] per layer
+    Returns dict matching existing outputs format but with 1-row matrices.
+    """
+    outputs = {}
+    for block_idx, layer_attn in enumerate(attentions):
+        # layer_attn shape: [1, 12, query_len, key_len]
+        for head_idx in range(12):
+            # Last token's attention row → shape [1, key_len]
+            scores = layer_attn[0, head_idx, -1, :].tolist()
+            key = f"block_{block_idx}_attn_head_{head_idx}_attn_dropout"
+            outputs[key] = {
+                "data": [scores],  # [[score0, score1, ...]] — 1×N
+                "dims": [1, len(scores)],
+                "size": len(scores)
+            }
+    return outputs
+
+def run_prefill(model, tokenizer, prompt):
+    """Run prefill and return token info + model output with past_key_values."""
+    inputs = tokenizer(prompt, return_tensors="pt")
+    token_ids = inputs["input_ids"][0].tolist()
+    tokens = [tokenizer.decode([tid]) for tid in token_ids]
+
+    with torch.no_grad():
+        output = model(
+            **inputs,
+            output_attentions=True,
+            use_cache=True
+        )
+
+    logits = output.logits[0, -1, :].tolist()  # last token logits → [50257]
+    past_key_values = output.past_key_values
+    prompt_kv = extract_head_vectors(past_key_values)
+
+    return {
+        "tokens": tokens,
+        "token_ids": token_ids,
+        "logits": logits,
+        "prompt_kv": prompt_kv,
+        "past_key_values": past_key_values,
+    }
+
+def run_decode_step(model, tokenizer, token_id, past_key_values):
+    """Run one decode step given a new token id and the current KV cache."""
+    input_ids = torch.tensor([[token_id]])
+
+    with torch.no_grad():
+        output = model(
+            input_ids=input_ids,
+            past_key_values=past_key_values,
+            output_attentions=True,
+            use_cache=True
+        )
+
+    next_token_id = output.logits[0, -1, :].argmax().item()
+    logits = output.logits[0, -1, :].tolist()
+    new_past_key_values = output.past_key_values
+
+    # KV cache now contains all tokens (prompt + all generated so far)
+    kv_snapshot = extract_head_vectors(new_past_key_values)
+    seq_len = new_past_key_values[0][0].shape[2]
+    attention_outputs = extract_attention_scores(output.attentions, seq_len)
+
+    return {
+        "input_token": tokenizer.decode([token_id]),
+        "input_token_id": token_id,
+        "next_token_id": next_token_id,
+        "logits": logits,
+        "kv_snapshot": kv_snapshot,   # K,V for ALL tokens so far
+        "attention_outputs": attention_outputs,
+        "past_key_values": new_past_key_values,
+    }
+
+def build_example(model, tokenizer, prompt):
+    """
+    Build decode steps only. Prefill display reuses the existing ex0-ex4 ONNX examples
+    which already have full intermediate activations. This script only needs to produce
+    the decode step data (KV snapshots + attention scores + logits).
+    """
+    print(f"  Prefill: {prompt!r}")
+    prefill = run_prefill(model, tokenizer, prompt)
+
+    # First decode token = argmax of prefill logits
+    first_token_id = int(torch.tensor(prefill["logits"]).argmax().item())
+    past = prefill["past_key_values"]
+    prompt_tokens = prefill["tokens"]
+
+    decode_steps = []
+    current_token_id = first_token_id
+
+    for step in range(DECODE_STEPS):
+        print(f"  Decode step {step + 1}: token_id={current_token_id} ({tokenizer.decode([current_token_id])!r})")
+        result = run_decode_step(model, tokenizer, current_token_id, past)
+        decode_steps.append({
+            "inputToken": result["input_token"],
+            "inputTokenId": result["input_token_id"],
+            "kvSnapshot": result["kv_snapshot"],
+            "attentionOutputs": result["attention_outputs"],
+            "logits": result["logits"],
+        })
+        past = result["past_key_values"]
+        current_token_id = result["next_token_id"]
+
+    # Only return decode steps — prefill display is handled by existing ex0-ex4 ONNX data
+    return {
+        "promptTokens": prompt_tokens,
+        "decodeSteps": decode_steps,
+    }
+
+def write_js(example, var_name, path):
+    """Write example as a JS module."""
+    data_json = json.dumps(example, separators=(',', ':'))
+    js = f"export const {var_name} = {data_json};\n"
+    with open(path, "w") as f:
+        f.write(js)
+    size_kb = os.path.getsize(path) / 1024
+    print(f"  Written {path} ({size_kb:.1f} KB)")
+
+def main():
+    os.makedirs(OUTPUT_DIR, exist_ok=True)
+
+    print("Loading GPT-2...")
+    tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+    model = GPT2LMHeadModel.from_pretrained("gpt2")
+    model.eval()
+
+    for i, prompt in enumerate(PROMPTS):
+        print(f"\nExample {i}: {prompt!r}")
+        example = build_example(model, tokenizer, prompt)
+        var_name = f"kvEx{i}"
+        path = os.path.join(OUTPUT_DIR, f"ex{i}.js")
+        write_js(example, var_name, path)
+
+    # Write index
+    imports = "\n".join(f"import {{kvEx{i}}} from './ex{i}';" for i in range(5))
+    exports = ", ".join(f"kvEx{i}" for i in range(5))
+    index_js = f"{imports}\n\nexport {{ {exports} }};\n"
+    with open(os.path.join(OUTPUT_DIR, "index.js"), "w") as f:
+        f.write(index_js)
+    print(f"\nWritten {OUTPUT_DIR}/index.js")
+    print("\nDone.")
+
+if __name__ == "__main__":
+    main()
+```
+
+- [ ] **Step 3: Run the script from the repo root**
+
+```bash
+cd /path/to/transformer-explainer
+python scripts/generate_kv_examples.py
+```
+
+Expected output:
+```
+Loading GPT-2...
+
+Example 0: 'Data visualization empowers users to'
+  Prefill: 'Data visualization empowers users to'
+  Decode step 1: token_id=15057 (' visualize')
+  Decode step 2: ...
+  Written src/constants/examples/kv/ex0.js (XXX KB)
+...
+Written src/constants/examples/kv/index.js
+Done.
+```
+
+- [ ] **Step 4: Verify the output structure**
+
+```bash
+node -e "
+const {kvEx0} = require('./src/constants/examples/kv/ex0.js');
+// Node won't parse ES modules — just check file exists and looks right
+" 2>/dev/null || head -1 src/constants/examples/kv/ex0.js
+```
+
+Expected: first line starts with `export const kvEx0 = {`
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add scripts/generate_kv_examples.py src/constants/examples/kv/
+git commit -m "feat: add KV cache example data and generation script"
+```
+
+---
+
+## Task 2: KV cache store
+
+**Files:**
+- Create: `src/store/kvcache.ts`
+
+- [ ] **Step 1: Create the store**
+
+Create `src/store/kvcache.ts`:
+
+```typescript
+import { writable, derived } from 'svelte/store';
+
+// Which decode step we're viewing. 0 = prefill complete, 1+ = decode steps.
+export const decodeStep = writable<number>(0);
+
+// Each entry is one token's K and V vectors for the currently selected head.
+// Shape per entry: { token: string, keys: number[], values: number[] }
+// keys/values are [head_dim=64] for the selected head.
+export type KVCacheEntry = {
+  token: string;
+  keys: number[];    // length 64
+  values: number[];  // length 64
+};
+
+export const kvCache = writable<KVCacheEntry[]>([]);
+
+// True after first decode step is loaded
+export const isDecoding = derived(decodeStep, ($s) => $s > 0);
+
+// Full data for the currently displayed decode step
+export type DecodeStepData = {
+  inputToken: string;
+  inputTokenId: number;
+  kvSnapshot: {
+    keys: number[][][];   // [12 heads, seq_len, 64]
+    values: number[][][]; // [12 heads, seq_len, 64]
+  };
+  attentionOutputs: Record<string, { data: number[][]; dims: number[]; size: number }>;
+  logits: number[];
+};
+
+export const currentDecodeData = writable<DecodeStepData | null>(null);
+
+// How many entries in kvCache are prompt tokens (styled differently in KVCacheTable)
+export const promptTokenCount = writable<number>(0);
+
+// Reset all KV cache state (called when user changes example or re-runs prefill)
+export function resetKVCache() {
+  decodeStep.set(0);
+  kvCache.set([]);
+  currentDecodeData.set(null);
+  promptTokenCount.set(0);
+}
+```
+
+- [ ] **Step 2: Commit**
+
+```bash
+git add src/store/kvcache.ts
+git commit -m "feat: add kvcache store for decode step state"
+```
+
+---
+
+## Task 3: KVCacheTable component
+
+**Files:**
+- Create: `src/components/KVCacheTable.svelte`
+
+This component renders the growing token × K/V table. Each row is a token. Columns are the token label, K vector (red VectorCanvas), and V vector (green VectorCanvas). New rows animate in with GSAP.
+
+- [ ] **Step 1: Create the component**
+
+Create `src/components/KVCacheTable.svelte`:
+
+```svelte
+<script lang="ts">
+  import { kvCache, type KVCacheEntry } from '~/store/kvcache';
+  import VectorCanvas from '~/components/common/VectorCanvas.svelte';
+  import { gsap } from '~/utils/gsap';
+  import { afterUpdate } from 'svelte';
+
+  // Row elements for animation — indexed by cache length
+  let rowEls: HTMLDivElement[] = [];
+  let prevLength = 0;
+
+  afterUpdate(() => {
+    const currentLength = $kvCache.length;
+    if (currentLength > prevLength) {
+      // Animate the newly added row(s) in
+      for (let i = prevLength; i < currentLength; i++) {
+        const el = rowEls[i];
+        if (el) {
+          gsap.from(el, {
+            opacity: 0,
+            y: -8,
+            duration: 0.4,
+            ease: 'power2.out'
+          });
+        }
+      }
+    }
+    prevLength = currentLength;
+  });
+</script>
+
+<div class="kv-cache-table">
+  <div class="kv-header">
+    <span class="col-label token-col">Token</span>
+    <span class="col-label k-col" style="color: var(--color-key)">K</span>
+    <span class="col-label v-col" style="color: var(--color-value)">V</span>
+  </div>
+
+  {#each $kvCache as entry, i}
+    <div
+      class="kv-row"
+      class:prompt-token={i < entry.promptCount}
+      bind:this={rowEls[i]}
+    >
+      <span class="token-label">{entry.token}</span>
+      <div class="vector-cell k-vector">
+        <VectorCanvas data={entry.keys} colorScale="red" />
+      </div>
+      <div class="vector-cell v-vector">
+        <VectorCanvas data={entry.values} colorScale="green" />
+      </div>
+    </div>
+  {/each}
+
+  {#if $kvCache.length === 0}
+    <div class="empty-hint">KV cache will populate after prefill</div>
+  {/if}
+</div>
+
+<style lang="scss">
+  .kv-cache-table {
+    display: flex;
+    flex-direction: column;
+    gap: 2px;
+    font-size: 0.7rem;
+    min-width: 12rem;
+  }
+
+  .kv-header {
+    display: grid;
+    grid-template-columns: 3rem 1fr 1fr;
+    gap: 4px;
+    padding-bottom: 4px;
+    border-bottom: 1px solid theme('colors.gray.200');
+    font-size: 0.65rem;
+    font-weight: 600;
+    color: theme('colors.gray.500');
+  }
+
+  .col-label {
+    text-align: center;
+  }
+
+  .kv-row {
+    display: grid;
+    grid-template-columns: 3rem 1fr 1fr;
+    gap: 4px;
+    align-items: center;
+    height: var(--vector-height, 16px);
+
+    &.prompt-token {
+      opacity: 0.7;
+    }
+  }
+
+  .token-label {
+    font-size: 0.65rem;
+    color: theme('colors.gray.600');
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+    text-align: right;
+    padding-right: 4px;
+  }
+
+  .vector-cell {
+    height: var(--vector-height, 16px);
+    position: relative;
+    overflow: hidden;
+  }
+
+  .empty-hint {
+    color: theme('colors.gray.400');
+    font-size: 0.65rem;
+    text-align: center;
+    padding: 0.5rem 0;
+  }
+</style>
+```
+
+> **Note:** `entry.promptCount` doesn't exist in `KVCacheEntry` yet — remove that line; we'll use a prop instead. Here's the corrected component — replace `class:prompt-token={i < entry.promptCount}` with `class:prompt-token={i < promptTokenCount}` and add `export let promptTokenCount: number = 0;` at the top of the script.
+
+Corrected `src/components/KVCacheTable.svelte`:
+
+```svelte
+<script lang="ts">
+  import { kvCache, promptTokenCount } from '~/store/kvcache';
+  import VectorCanvas from '~/components/common/VectorCanvas.svelte';
+  import { gsap } from '~/utils/gsap';
+  import { afterUpdate } from 'svelte';
+
+  let rowEls: (HTMLDivElement | undefined)[] = [];
+  let prevLength = 0;
+
+  afterUpdate(() => {
+    const currentLength = $kvCache.length;
+    if (currentLength > prevLength) {
+      for (let i = prevLength; i < currentLength; i++) {
+        const el = rowEls[i];
+        if (el) {
+          gsap.from(el, { opacity: 0, y: -8, duration: 0.4, ease: 'power2.out' });
+        }
+      }
+    }
+    prevLength = currentLength;
+  });
+</script>
+
+<div class="kv-cache-table">
+  <div class="kv-header">
+    <span class="col-label">Token</span>
+    <span class="col-label k-col">K</span>
+    <span class="col-label v-col">V</span>
+  </div>
+
+  {#each $kvCache as entry, i}
+    <div class="kv-row" class:prompt-token={i < $promptTokenCount} bind:this={rowEls[i]}>
+      <span class="token-label">{entry.token}</span>
+      <div class="vector-cell">
+        <VectorCanvas data={entry.keys} colorScale="red" />
+      </div>
+      <div class="vector-cell">
+        <VectorCanvas data={entry.values} colorScale="green" />
+      </div>
+    </div>
+  {/each}
+
+  {#if $kvCache.length === 0}
+    <div class="empty-hint">KV cache populates after prefill</div>
+  {/if}
+</div>
+
+<style lang="scss">
+  .kv-cache-table {
+    display: flex;
+    flex-direction: column;
+    gap: 2px;
+    font-size: 0.7rem;
+    min-width: 12rem;
+  }
+  .kv-header {
+    display: grid;
+    grid-template-columns: 3rem 1fr 1fr;
+    gap: 4px;
+    padding-bottom: 4px;
+    border-bottom: 1px solid theme('colors.gray.200');
+    font-size: 0.65rem;
+    font-weight: 600;
+    color: theme('colors.gray.500');
+  }
+  .k-col { color: theme('colors.red.400'); }
+  .v-col { color: theme('colors.green.400'); }
+  .col-label { text-align: center; }
+  .kv-row {
+    display: grid;
+    grid-template-columns: 3rem 1fr 1fr;
+    gap: 4px;
+    align-items: center;
+    height: var(--vector-height, 16px);
+    &.prompt-token { opacity: 0.7; }
+  }
+  .token-label {
+    font-size: 0.65rem;
+    color: theme('colors.gray.600');
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+    text-align: right;
+    padding-right: 4px;
+  }
+  .vector-cell {
+    height: var(--vector-height, 16px);
+    position: relative;
+    overflow: hidden;
+  }
+  .empty-hint {
+    color: theme('colors.gray.400');
+    font-size: 0.65rem;
+    text-align: center;
+    padding: 0.5rem 0;
+  }
+</style>
+```
+
+- [ ] **Step 2: Commit**
+
+```bash
+git add src/components/KVCacheTable.svelte
+git commit -m "feat: add KVCacheTable component for growing cache visualization"
+```
+
+---
+
+## Task 4: Modify AttentionMatrix for decode mode
+
+**Files:**
+- Modify: `src/components/AttentionMatrix.svelte`
+
+Add decode mode: import `isDecoding` and `currentDecodeData` from the kvcache store. When `$isDecoding` is true, render a 1×N attention strip and the KVCacheTable instead of the N×N matrix.
+
+- [ ] **Step 1: Add imports to the existing script block**
+
+In `src/components/AttentionMatrix.svelte`, after the last existing import line (currently line 28: `import { highlightAttentionPath, removeAttentionPathHighlight } from '~/utils/textbook';`), add:
+
+```typescript
+import { isDecoding, currentDecodeData } from '~/store/kvcache';
+import KVCacheTable from '~/components/KVCacheTable.svelte';
+import { tokens } from '~/store';
+```
+
+- [ ] **Step 2: Add decode-mode reactive data**
+
+After the existing `$: softmaxed = ...` block (around line 43), add:
+
+```typescript
+// Decode mode: 1×N attention scores for the current decode token
+$: decodeAttentionRow =
+  $currentDecodeData?.attentionOutputs?.[
+    `block_${$blockIdx}_attn_head_${$attentionHeadIdx}_attn_dropout`
+  ]?.data ?? [[]];
+```
+
+- [ ] **Step 3: Wrap the existing template in a conditional**
+
+In the template section of `AttentionMatrix.svelte`, find the outermost wrapper div (the one with `bind:this={expandableEl}`). Wrap the entire existing matrix HTML in `{#if !$isDecoding}...{/if}` and add an `{:else}` block for decode mode.
+
+The structure should be:
+
+```svelte
+<div class="attention-matrix-wrapper" bind:this={expandableEl}>
+  {#if !$isDecoding}
+    <!-- === EXISTING N×N CONTENT — untouched === -->
+    <!-- (all the existing HTML stays here, no changes) -->
+
+  {:else}
+    <!-- === DECODE MODE: 1×N strip + KVCacheTable === -->
+    <div class="decode-mode flex flex-col gap-2">
+      <div class="decode-strip-label text-xs text-gray-500">
+        Attention (1 × {$tokens.length + ($decodeStep ?? 0)} — new token → cached tokens)
+      </div>
+
+      <!-- 1×N attention strip using existing Matrix component -->
+      <div class="decode-attention-strip">
+        <div class="kv-cache-bracket-label text-xs text-red-400">KV Cache ←</div>
+        <Matrix
+          data={decodeAttentionRow}
+          showSize={false}
+          cellHeight={cellSize}
+          cellWidth={cellSize}
+          rowGap={3}
+          colGap={3}
+          shape={'circle'}
+          colorScale={qkColorScale}
+          onMouseOverCell={onMouseOverCell}
+          onMouseOutCell={onMouseOutCell}
+          showTooltip={showTooltip}
+        />
+        <div class="new-token-label text-xs text-blue-400">← New</div>
+      </div>
+
+      <!-- Growing KV cache table (promptTokenCount set in kvcache store) -->
+      <KVCacheTable />
+    </div>
+  {/if}
+</div>
+```
+
+Also add `import { decodeStep } from '~/store/kvcache';` to the imports.
+
+- [ ] **Step 4: Add decode mode styles**
+
+In the `<style>` block of `AttentionMatrix.svelte`, add:
+
+```scss
+.decode-mode {
+  padding: 0.5rem;
+  min-width: 10rem;
+}
+
+.decode-attention-strip {
+  display: flex;
+  flex-direction: column;
+  align-items: flex-start;
+  gap: 2px;
+}
+
+.kv-cache-bracket-label,
+.new-token-label {
+  font-size: 0.6rem;
+  line-height: 1;
+}
+```
+
+- [ ] **Step 5: Commit**
+
+```bash
+git add src/components/AttentionMatrix.svelte
+git commit -m "feat: add decode mode to AttentionMatrix (1xN strip + KVCacheTable)"
+```
+
+---
+
+## Task 5: Create the kv-cache route
+
+**Files:**
+- Create: `src/routes/kv-cache/+page.ts`
+- Create: `src/routes/kv-cache/+page.svelte`
+
+The page is a copy of the root page with these differences:
+1. Imports KV examples (`kvEx0`–`kvEx4`) instead of (`ex0`–`ex4`)
+2. After `fakeRunWithCachedData` completes, activates decode mode controls
+3. Adds `← Prev` / `Next →` buttons for stepping through decode
+4. Has a header note explaining KV cache mode
+
+- [ ] **Step 1: Create the page loader**
+
+Create `src/routes/kv-cache/+page.ts`:
+
+```typescript
+export const prerender = true;
+```
+
+- [ ] **Step 2: Create the page**
+
+Create `src/routes/kv-cache/+page.svelte`. Start from the root page and make these targeted changes:
+
+```svelte
+<script lang="ts">
+  import {
+    tokens,
+    expandedBlock,
+    vectorHeight,
+    inputText,
+    rootRem,
+    sampling,
+    maxVectorHeight,
+    minVectorHeight,
+    maxVectorScale,
+    headContentHeight,
+    temperature,
+    modelData,
+    modelSession,
+    isFetchingModel,
+    selectedExampleIdx,
+    isMobile,
+    isOnBlockTransition,
+    blockIdx,
+    isTextbookOpen,
+    userId
+  } from '~/store';
+  import { PreTrainedTokenizer } from '@xenova/transformers';
+  import Sankey from '~/components/Sankey.svelte';
+  import Attention from '~/components/Attention.svelte';
+  import SubsequentBlocks from '~/components/SubsequentBlocks.svelte';
+  import LinearSoftmax from '~/components/LinearSoftmax.svelte';
+  import Embedding from '~/components/Embedding.svelte';
+  import Mlp from '~/components/Mlp.svelte';
+
+  import { onMount } from 'svelte';
+  import classNames from 'classnames';
+  import { base } from '$app/paths';
+  import * as ort from 'onnxruntime-web';
+
+  import { adjustTemperature, fakeRunWithCachedData } from '~/utils/data';
+  import WeightPopovers from '~/components/WeightPopovers.svelte';
+  import { fade } from 'svelte/transition';
+  import { AutoTokenizer } from '@xenova/transformers';
+  import BlockTransition from '~/components/BlockTransition.svelte';
+  import QKV from '~/components/QKV.svelte';
+  import Textbook from '~/components/textbook/Textbook.svelte';
+
+  // Existing examples for prefill display (have full ONNX intermediate outputs)
+  import { ex0, ex1, ex2, ex3, ex4 } from '~/constants/examples';
+  // KV decode-step data (decode steps only, generated by scripts/generate_kv_examples.py)
+  import { kvEx0, kvEx1, kvEx2, kvEx3, kvEx4 } from '~/constants/examples/kv';
+  import {
+    decodeStep,
+    kvCache,
+    isDecoding,
+    currentDecodeData,
+    promptTokenCount,
+    resetKVCache,
+    type KVCacheEntry
+  } from '~/store/kvcache';
+  import { attentionHeadIdx } from '~/store';
+
+  ort.env.wasm.wasmPaths = 'https://cdn.jsdelivr.net/npm/onnxruntime-web@1.23.0/dist/';
+  ort.env.logLevel = 'error';
+
+  let active = false;
+
+  // Prefill examples (existing, full ONNX outputs)
+  const prefillExamples = [ex0, ex1, ex2, ex3, ex4];
+  // Decode step examples (KV-specific, decode steps only)
+  const kvExamples = [kvEx0, kvEx1, kvEx2, kvEx3, kvEx4];
+
+  $: currentPrefillExample = prefillExamples[$selectedExampleIdx];
+  $: currentKVExample = kvExamples[$selectedExampleIdx];
+
+  onMount(async () => {
+    const gpt2Tokenizer = await AutoTokenizer.from_pretrained('Xenova/gpt2');
+    active = true;
+    const unsubscribe = subscribeInputs(gpt2Tokenizer);
+    return unsubscribe;
+  });
+
+  const subscribeInputs = (tokenizer: PreTrainedTokenizer) => {
+    const runPrefill = () => {
+      resetKVCache();
+      // Use existing ex0-ex4 for prefill — they have full ONNX intermediate activations
+      const cachedData = prefillExamples[$selectedExampleIdx];
+      promptTokenCount.set(cachedData.tokens.length);
+      fakeRunWithCachedData({
+        cachedData,
+        tokenizer,
+        temperature: $temperature,
+        sampling: $sampling
+      });
+    };
+
+    const unsubscribeInputText = inputText.subscribe(() => runPrefill());
+
+    let initialTemperature = true;
+    const unsubscribeTemperature = temperature.subscribe((value) => {
+      if (initialTemperature) { initialTemperature = false; return; }
+      if ($isDecoding && $currentDecodeData) {
+        adjustTemperature({ tokenizer, logits: $currentDecodeData.logits, temperature: value, sampling: $sampling });
+      } else {
+        adjustTemperature({ tokenizer, logits: $modelData.logits, temperature: value, sampling: $sampling });
+      }
+    });
+
+    let initialSampling = true;
+    const unsubscribeSampling = sampling.subscribe((value) => {
+      if (initialSampling) { initialSampling = false; return; }
+      const logits = $isDecoding && $currentDecodeData ? $currentDecodeData.logits : $modelData.logits;
+      adjustTemperature({ tokenizer, logits, temperature: $temperature, sampling: value });
+    });
+
+    return () => {
+      unsubscribeInputText();
+      unsubscribeTemperature();
+      unsubscribeSampling();
+    };
+  };
+
+  // Build KV cache entries for a given head from a kvSnapshot
+  function buildCacheEntries(
+    tokenList: string[],
+    kvSnapshot: { keys: number[][][]; values: number[][][] },
+    headIdx: number
+  ): KVCacheEntry[] {
+    return tokenList.map((token, i) => ({
+      token,
+      keys: kvSnapshot.keys[headIdx][i],
+      values: kvSnapshot.values[headIdx][i]
+    }));
+  }
+
+  function advanceDecodeStep() {
+    const example = currentKVExample;
+    const nextStep = $decodeStep + 1;
+    if (nextStep > example.decodeSteps.length) return;
+
+    const stepData = example.decodeSteps[nextStep - 1];
+    decodeStep.set(nextStep);
+    currentDecodeData.set(stepData);
+
+    // Tokens shown: prompt tokens + all decode input tokens so far
+    const promptTokens = example.promptTokens;
+    const decodeTokens = example.decodeSteps
+      .slice(0, nextStep)
+      .map((s: { inputToken: string }) => s.inputToken);
+    const allTokens = [...promptTokens, ...decodeTokens];
+    tokens.set(allTokens);
+
+    // Update KV cache entries for the currently selected head
+    kvCache.set(
+      buildCacheEntries(allTokens, stepData.kvSnapshot, $attentionHeadIdx)
+    );
+
+    // Update modelData outputs so AttentionMatrix decode strip has data
+    modelData.update((md) => ({
+      ...md,
+      logits: stepData.logits,
+      outputs: { ...md.outputs, ...stepData.attentionOutputs }
+    }));
+  }
+
+  function retreatDecodeStep(tokenizer: PreTrainedTokenizer) {
+    if ($decodeStep <= 0) return;
+    const prevStep = $decodeStep - 1;
+
+    if (prevStep === 0) {
+      // Go back to prefill — use existing ex0-ex4 (full ONNX outputs)
+      resetKVCache();
+      const cachedData = currentPrefillExample;
+      promptTokenCount.set(cachedData.tokens.length);
+      fakeRunWithCachedData({ cachedData, tokenizer, temperature: $temperature, sampling: $sampling });
+      return;
+    }
+
+    const stepData = currentKVExample.decodeSteps[prevStep - 1];
+    decodeStep.set(prevStep);
+    currentDecodeData.set(stepData);
+
+    const promptTokens = currentKVExample.promptTokens;
+    const decodeTokens = currentKVExample.decodeSteps
+      .slice(0, prevStep)
+      .map((s: { inputToken: string }) => s.inputToken);
+    const allTokens = [...promptTokens, ...decodeTokens];
+    tokens.set(allTokens);
+
+    kvCache.set(
+      buildCacheEntries(allTokens, stepData.kvSnapshot, $attentionHeadIdx)
+    );
+
+    modelData.update((md) => ({
+      ...md,
+      logits: stepData.logits,
+      outputs: { ...md.outputs, ...stepData.attentionOutputs }
+    }));
+  }
+
+  // Also update KV cache entries when attentionHeadIdx changes (head selector)
+  $: if ($isDecoding && $currentDecodeData) {
+    const promptTokens = currentKVExample.promptTokens;
+    const decodeTokens = currentKVExample.decodeSteps
+      .slice(0, $decodeStep)
+      .map((s: { inputToken: string }) => s.inputToken);
+    const allTokens = [...promptTokens, ...decodeTokens];
+    kvCache.set(
+      buildCacheEntries(allTokens, $currentDecodeData.kvSnapshot, $attentionHeadIdx)
+    );
+  }
+
+  let tokenizer: PreTrainedTokenizer | null = null;
+  onMount(async () => {
+    tokenizer = await AutoTokenizer.from_pretrained('Xenova/gpt2');
+  });
+
+  // visual elements
+  let vizHeight = 0;
+  let titleHeight = rootRem * 5;
+
+  const calculateVectorHeight = () => {
+    const gaps = rootRem * 0.5 * ($tokens.length - 1);
+    const vectorHeightVal = Math.min(
+      Math.max((vizHeight - titleHeight - gaps) / $tokens.length / maxVectorScale, minVectorHeight),
+      maxVectorHeight
+    );
+    vectorHeight.set(vectorHeightVal);
+    headContentHeight.set(Math.max($tokens.length * vectorHeightVal * 3 + gaps, rootRem * 20));
+  };
+
+  $: if (vizHeight || $tokens.length) {
+    calculateVectorHeight();
+  }
+
+  $: maxDecodeStep = currentKVExample?.decodeSteps?.length ?? 0;
+</script>
+
+<div
+  class:active
+  class="main-section h-full w-full"
+  style={`--vector-height: ${$vectorHeight}px;--title-height: ${titleHeight}px;--content-height:${vizHeight - titleHeight}px;`}
+>
+  <!-- KV Cache mode banner -->
+  <div class="kv-mode-banner text-xs text-purple-600 text-center py-1 bg-purple-50 border-b border-purple-100">
+    KV Cache Mode — prefill shows N×N attention, decode steps show cached K/V + 1×N attention
+    {#if $isDecoding}
+      · Decode step {$decodeStep}/{maxDecodeStep}
+    {/if}
+  </div>
+
+  {#if !!$expandedBlock.id}
+    <div class={classNames('dim', `${$expandedBlock.id || ''}`)} transition:fade={{ duration: 100 }}></div>
+    <div class={classNames('dim-partial left', `${$expandedBlock.id || ''}`)} transition:fade={{ duration: 100 }}></div>
+    <div class={classNames('dim-partial right', `${$expandedBlock.id || ''}`)} transition:fade={{ duration: 100 }}></div>
+  {/if}
+
+  <div class="sankey opacity-1" class:attention={$expandedBlock.id === 'attention'}>
+    <Sankey />
+  </div>
+
+  <div class="nodes resize-watch">
+    <div class="steps" class:expanded={!!$expandedBlock.id} bind:offsetHeight={vizHeight}>
+      <Embedding className="step" />
+      <div class="blocks relative">
+        <div class="block-steps main" class:initial={$blockIdx === 0}>
+          <QKV className="step" />
+          <Attention className="step" />
+          <Mlp className="step" />
+        </div>
+        <div class="block-steps next" class:hide={!$isOnBlockTransition} class:initial={$blockIdx === 0}>
+          <QKV className="step" />
+          <Attention className="step" />
+          <Mlp className="step" />
+        </div>
+        <div class="transition-watch" class:hide={!$isOnBlockTransition}></div>
+      </div>
+      <SubsequentBlocks className="step" />
+      <LinearSoftmax className="step" />
+    </div>
+
+    <WeightPopovers />
+    <BlockTransition />
+
+    {#if !$isMobile}
+      <Textbook showTextCard={$isTextbookOpen} />
+    {/if}
+
+    <!-- Decode step controls — shown after first token is generated -->
+    {#if active}
+      <div class="decode-controls" class:visible={true} transition:fade={{ duration: 200 }}>
+        <button
+          class="step-btn"
+          disabled={$decodeStep <= 0}
+          on:click={() => tokenizer && retreatDecodeStep(tokenizer)}
+        >
+          ← Prev
+        </button>
+        <span class="step-indicator">
+          {#if $isDecoding}
+            Decode {$decodeStep}/{maxDecodeStep}
+          {:else}
+            Prefill
+          {/if}
+        </span>
+        <button
+          class="step-btn"
+          disabled={$decodeStep >= maxDecodeStep}
+          on:click={advanceDecodeStep}
+        >
+          Next →
+        </button>
+      </div>
+    {/if}
+  </div>
+</div>
+
+<style lang="scss">
+  .main-section {
+    opacity: 0;
+    &.active { opacity: 1; }
+  }
+  .kv-mode-banner {
+    position: sticky;
+    top: 0;
+    z-index: $TOP_BAR_INDEX - 1;
+  }
+  .nodes {
+    height: 100%;
+    width: 100%;
+    padding: 1rem 0 3rem 0;
+    position: relative;
+  }
+  .steps {
+    position: relative;
+    width: 100%;
+    height: 100%;
+    display: grid;
+    grid-template-columns: auto 3.5fr 0.5fr 0.5fr;
+    &.expanded {
+      :global(.step > .title) { padding-bottom: 3rem; }
+    }
+    .blocks {
+      position: relative;
+      width: 100%;
+      height: 100%;
+      .block-steps {
+        height: 100%;
+        width: 100%;
+        position: absolute;
+        display: grid;
+        grid-template-columns: 0.5fr 2fr 1fr;
+      }
+      .block-steps.main {
+        transform-origin: 3rem center;
+        top: 0;
+        left: 0;
+      }
+    }
+  }
+  .decode-controls {
+    position: fixed;
+    bottom: 1.5rem;
+    left: 50%;
+    transform: translateX(-50%);
+    display: flex;
+    align-items: center;
+    gap: 0.75rem;
+    background: white;
+    border: 1px solid theme('colors.purple.200');
+    border-radius: 2rem;
+    padding: 0.4rem 1rem;
+    box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+    z-index: $TOP_BAR_INDEX - 2;
+  }
+  .step-btn {
+    font-size: 0.75rem;
+    color: theme('colors.purple.600');
+    background: none;
+    border: none;
+    cursor: pointer;
+    padding: 0.2rem 0.4rem;
+    border-radius: 0.25rem;
+    &:disabled {
+      color: theme('colors.gray.300');
+      cursor: default;
+    }
+    &:not(:disabled):hover {
+      background: theme('colors.purple.50');
+    }
+  }
+  .step-indicator {
+    font-size: 0.7rem;
+    color: theme('colors.gray.500');
+    min-width: 6rem;
+    text-align: center;
+  }
+</style>
+```
+
+> **Note:** The `onMount` is called twice in the above — combine them into one. Final version:
+
+Replace the two separate `onMount` calls with:
+
+```typescript
+onMount(async () => {
+  tokenizer = await AutoTokenizer.from_pretrained('Xenova/gpt2');
+  active = true;
+  const unsubscribe = subscribeInputs(tokenizer);
+  return unsubscribe;
+});
+```
+
+And remove `let tokenizer` above onMount — move it inside the script with the others.
+
+- [ ] **Step 3: Commit**
+
+```bash
+git add src/routes/kv-cache/
+git commit -m "feat: add /kv-cache route with decode step controls"
+```
+
+---
+
+## Task 6: Update svelte.config.js prerender entries
+
+**Files:**
+- Modify: `svelte.config.js`
+
+- [ ] **Step 1: Add /kv-cache to prerender entries**
+
+In `svelte.config.js`, change line 24 from:
+
+```js
+entries: ['/' /* other routes if needed */]
+```
+
+to:
+
+```js
+entries: ['/', '/kv-cache']
+```
+
+- [ ] **Step 2: Commit**
+
+```bash
+git add svelte.config.js
+git commit -m "chore: add /kv-cache to prerender entries"
+```
+
+---
+
+## Task 7: Manual verification
+
+No automated tests exist in this repo. Verify by running the dev server.
+
+- [ ] **Step 1: Install dependencies and start dev server**
+
+```bash
+npm install
+npm run dev
+```
+
+Expected: server starts at `http://localhost:5173`
+
+- [ ] **Step 2: Verify root page is unchanged**
+
+Navigate to `http://localhost:5173/`. Confirm the original transformer explainer loads and functions exactly as before. Generate a token and confirm the N×N attention matrix appears as usual.
+
+- [ ] **Step 3: Verify KV cache page loads**
+
+Navigate to `http://localhost:5173/kv-cache`. Confirm:
+- The purple banner "KV Cache Mode" is visible at the top
+- The transformer visualization loads with the first example
+- The prefill N×N attention matrix shows (same as root page)
+- "Prev / Prefill / Next" controls appear at the bottom
+
+- [ ] **Step 4: Verify decode step advance**
+
+Click "Next →". Confirm:
+- Banner updates to "Decode step 1/5"
+- Attention panel switches to the 1×N attention strip
+- KVCacheTable appears below the strip, populated with prompt tokens' K (red) and V (green) vectors
+- Each subsequent "Next →" animates a new row into the KVCacheTable
+
+- [ ] **Step 5: Verify "Prev" navigation**
+
+Click "← Prev" from a decode step. Confirm:
+- Stepping back to Decode step 1 from step 2 restores the correct state
+- Stepping back to Prefill from step 1 shows the N×N matrix again and clears the KVCacheTable
+
+- [ ] **Step 6: Verify temperature/sampling controls**
+
+Change temperature slider while on a decode step. Confirm the Probabilities panel updates (top-k token probabilities change) without resetting the decode step.
+
+- [ ] **Step 7: Verify head selector**
+
+Change the attention head (0–11) while on a decode step. Confirm the KVCacheTable updates to show the K and V vectors for the newly selected head.
+
+- [ ] **Step 8: Build and confirm prerender**
+
+```bash
+npm run build
+```
+
+Expected: build completes with no errors, and `build/kv-cache/index.html` exists.
+
+```bash
+ls build/kv-cache/
+```
+
+Expected output includes `index.html`.
+
+---
+
+## Task 8: Final commit and branch ready for PR
+
+- [ ] **Step 1: Verify git log**
+
+```bash
+git log --oneline main..HEAD
+```
+
+Expected (6 commits):
+```
+<hash> chore: add /kv-cache to prerender entries
+<hash> feat: add /kv-cache route with decode step controls
+<hash> feat: add decode mode to AttentionMatrix (1xN strip + KVCacheTable)
+<hash> feat: add KVCacheTable component for growing cache visualization
+<hash> feat: add kvcache store for decode step state
+<hash> feat: add KV cache example data and generation script
+<hash> Add KV cache explainer design spec
+```
+
+- [ ] **Step 2: Push branch**
+
+```bash
+git push -u origin kv-cache-explainer
+```
+
+- [ ] **Step 3: Open PR referencing issue #63**
+
+```bash
+gh pr create \
+  --repo poloclub/transformer-explainer \
+  --title "feat: add /kv-cache route with KV cache visualization" \
+  --body "$(cat <<'EOF'
+## Summary
+- Adds `/kv-cache` route at `poloclub.github.io/transformer-explainer/kv-cache`
+- Prefill phase shows existing N×N attention matrix (unchanged behavior)
+- Decode phase shows growing KV cache table (K in red, V in green per head) + 1×N attention strip
+- Step-through controls (← Prev / Next →) to walk through 5 decode steps per example
+- Temperature and sampling controls remain functional throughout
+- Root page (`/`) is completely untouched
+
+## How it works
+Pre-computed example data generated offline via `scripts/generate_kv_examples.py` (GPT-2 + HuggingFace). `AttentionMatrix.svelte` gains a reactive decode mode driven by `src/store/kvcache.ts`. New `KVCacheTable.svelte` component uses existing `VectorCanvas` with GSAP row animations.
+
+## Out of scope (follow-up)
+Live GPT-2 inference for the kv-cache page (same ONNX approach as main page).
+
+Closes #63
+
+🤖 Generated with [Claude Code](https://claude.ai/claude-code)
+EOF
+)"
+```
diff --git a/docs/superpowers/specs/2026-03-27-kvcache-explainer-design.md b/docs/superpowers/specs/2026-03-27-kvcache-explainer-design.md
new file mode 100644
index 0000000..d2c273a
--- /dev/null
+++ b/docs/superpowers/specs/2026-03-27-kvcache-explainer-design.md
@@ -0,0 +1,194 @@
+# KV Cache Explainer — Design Spec
+**Date:** 2026-03-27
+**Issue:** poloclub/transformer-explainer#63
+**Status:** Approved
+
+## Overview
+
+Add a `/kv-cache` route to the existing `transformer-explainer` repo that demonstrates
+the difference between prefill and decode phases, with an interactive KV cache visualization.
+The original `/` route is completely untouched.
+
+**URL:** `https://poloclub.github.io/transformer-explainer/kv-cache`
+
+---
+
+## Approach
+
+Option 1 (chosen): Duplicate and modify. Copy the root page into `src/routes/kv-cache/`,
+modify `AttentionMatrix.svelte` to accept a `decodeMode` prop, and build a new
+`KVCacheTable.svelte` component. All shared components (Embedding, MLP, LinearSoftmax,
+Sankey, stores) are imported as-is — no duplication of shared logic.
+
+---
+
+## File Changes
+
+### New files
+
+```
+src/routes/kv-cache/
+  +page.svelte            # Copy of root +page.svelte, modified for decode flow
+  +page.ts                # Copy of root +page.ts
+
+src/components/
+  KVCacheTable.svelte     # Growing cache table: token × (K vector, V vector)
+
+src/constants/examples/kv/
+  ex0.js                  # Pre-computed prefill + decode steps (prompt: "Data visualization empowers users to")
+  ex1.js                  # "Artificial Intelligence is transforming the"
+  ex2.js                  # "As the spaceship was approaching the"
+  ex3.js                  # "On the deserted planet they discovered a"
+  ex4.js                  # "IEEE VIS conference highlights the"
+
+src/store/kvcache.ts      # Decode-specific stores
+
+scripts/
+  generate_kv_examples.py # Offline script to generate example data from GPT-2 (not shipped)
+```
+
+### Modified files
+
+```
+src/components/AttentionMatrix.svelte   # Add decodeMode prop
+svelte.config.js                        # Add /kv-cache to prerender entries
+```
+
+---
+
+## Component Design
+
+### `AttentionMatrix.svelte` — modified
+
+New prop: `decodeMode: boolean` (default `false`).
+
+- `decodeMode = false`: existing N×N behavior, no change.
+- `decodeMode = true`:
+  - Hides the N×N matrix.
+  - Renders a **1×N attention strip** — one row for the current decode token's query
+    attending to all N cached tokens.
+  - Renders `<KVCacheTable>` below the strip.
+  - Labels: "KV Cache" bracket spanning cached tokens (prompt + previously generated);
+    "New" label on the current decode token.
+
+### `KVCacheTable.svelte` — new
+
+A table with one row per token seen so far. Three columns:
+- **Token label** — token string
+- **K vector** — rendered with existing `VectorCanvas`, red color scheme (matches existing K color)
+- **V vector** — rendered with existing `VectorCanvas`, green color scheme (matches existing V color)
+
+On each decode step advance, a new row animates in (GSAP tween, consistent with existing
+expand/collapse animations). Prompt tokens pre-populate on the first decode step.
+
+### `src/routes/kv-cache/+page.svelte` — new route
+
+Same layout as root page. Differences:
+- Passes `decodeMode={$isDecoding}` to `AttentionMatrix`.
+- Adds **"← Prev / Next →"** step controls (shown only after prefill completes).
+- Each step: advances `decodeStep` store, updates `kvCache`, `currentDecodeData`.
+- Temperature and Sampling controls remain active.
+
+---
+
+## Data Model
+
+### Example file format (`src/constants/examples/kv/ex0.js`)
+
+```js
+export default {
+  // Prefill — identical format to existing src/constants/examples/ex0.js
+  prefill: {
+    prompt: "Data visualization empowers users to",
+    tokens: ["Data", "▁visual", "ization", "▁empowers", "▁users", "▁to"],
+    tokenIds: [...],
+    logits: [...],      // (50257,) — first predicted token logits
+    outputs: { ... }    // per-layer/head activations, same keys as existing examples
+  },
+
+  // Decode steps — one entry per generated token (up to ~5 steps)
+  decodeSteps: [
+    {
+      inputToken: "▁visualize",
+      tokenId: 15057,
+      kvCache: {
+        // K and V for all tokens seen so far (prompt + previous decode tokens)
+        // shape per entry: [num_heads, head_dim] = [12, 64]
+        keys:   [...],   // array of length num_tokens_so_far, each (12, 64)
+        values: [...],   // same shape
+      },
+      attentionScores: [...],   // (1, num_tokens_so_far) — softmaxed scores
+      logits: [...],            // (50257,) — next token logits
+      outputs: { ... }          // per-layer activations for new token (same keys)
+    },
+    // ... up to ~5 steps
+  ]
+}
+```
+
+### Generation script (`scripts/generate_kv_examples.py`)
+
+Offline Python script using HuggingFace `transformers`. Runs GPT-2 on each prompt,
+extracts KV cache at each decode step using `past_key_values`, dumps JSON.
+Not shipped with the app — run once to produce the example `.js` files.
+
+---
+
+## State Management
+
+New file `src/store/kvcache.ts`. Does **not** modify `src/store/index.ts`.
+
+```ts
+export const decodeStep = writable<number>(0);
+// 0 = prefill complete, 1+ = decode steps
+
+export const kvCache = writable<{ token: string; keys: number[]; values: number[] }[]>([]);
+// Grows by one row per step advance
+
+export const isDecoding = derived(decodeStep, ($s) => $s > 0);
+
+export const currentDecodeData = writable<DecodeStep | null>(null);
+// Data for the currently displayed decode step
+
+// Reuses existing attentionHeadIdx from src/store/index.ts for head selection
+```
+
+Existing stores (`attentionHeadIdx`, `blockIdx`, `temperature`, `sampling`,
+`highlightedToken`, etc.) are imported and reused unchanged.
+
+---
+
+## User Flow
+
+1. User navigates to `/kv-cache` — sees the familiar transformer layout with a note
+   explaining KV cache mode.
+2. Selects an example or types a prompt → hits **Generate**.
+3. Prefill runs: existing N×N attention visualization shown (same as main page).
+4. First token predicted → decode mode activates automatically:
+   - Attention panel switches to 1×N strip + KVCacheTable.
+   - KVCacheTable populates with all prompt tokens' K (blue) and V (green) vectors.
+   - "KV Cache" bracket and "New" label appear.
+5. User clicks **Next →** to step through decode:
+   - New token row animates into KVCacheTable.
+   - 1×N attention strip updates to show new token's attention scores.
+   - Probabilities panel updates with next token predictions.
+6. Temperature and sampling controls affect probabilities panel in real time.
+7. Up to 5 decode steps supported in pre-computed examples.
+
+---
+
+## Out of Scope (follow-up PR)
+
+- Live GPT-2 inference via ONNX (same approach as main page).
+- Mobile support for decode mode (mirrors main page's mobile fallback).
+- Textbook/article content specific to KV cache (can be added incrementally).
+
+---
+
+## Styling
+
+Follows existing conventions exactly:
+- Tailwind utility classes, existing CSS variables, SCSS variables from `variables.scss`.
+- Colors: K vectors in `red-300`, V vectors in `green-300` (matches existing QKV color coding: Q=blue, K=red, V=green).
+- Animations: GSAP tweens consistent with existing expand/collapse patterns.
+- Font: Jersey 10 for display, system font for body — no changes.
diff --git a/package-lock.json b/package-lock.json
index e9a5887..aa8038f 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -48,7 +48,7 @@
 				"tailwindcss": "^3.4.1",
 				"tslib": "^2.4.1",
 				"typescript": "^5.0.0",
-				"vite": "^5.4.21"
+				"vite": "^6.3.0"
 			},
 			"engines": {
 				"node": ">=20.0.0",
@@ -69,9 +69,9 @@
 			}
 		},
 		"node_modules/@esbuild/aix-ppc64": {
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.25.12.tgz",
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 			"cpu": [
 				"ppc64"
 			],
@@ -82,13 +82,13 @@
 				"aix"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/android-arm": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/android-arm/-/android-arm-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/android-arm/-/android-arm-0.25.12.tgz",
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 			"cpu": [
 				"arm"
 			],
@@ -99,13 +99,13 @@
 				"android"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/android-arm64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/android-arm64/-/android-arm64-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/android-arm64/-/android-arm64-0.25.12.tgz",
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 			"cpu": [
 				"arm64"
 			],
@@ -116,13 +116,13 @@
 				"android"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/android-x64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/android-x64/-/android-x64-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/android-x64/-/android-x64-0.25.12.tgz",
+			"integrity": "sha512-5jbb+2hhDHx5phYR2By8GTWEzn6I9UqR11Kwf22iKbNpYrsmRB18aX/9ivc5cabcUiAT/wM+YIZ6SG9QO6a8kg==",
 			"cpu": [
 				"x64"
 			],
@@ -133,13 +133,13 @@
 				"android"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/darwin-arm64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/darwin-arm64/-/darwin-arm64-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/darwin-arm64/-/darwin-arm64-0.25.12.tgz",
+			"integrity": "sha512-N3zl+lxHCifgIlcMUP5016ESkeQjLj/959RxxNYIthIg+CQHInujFuXeWbWMgnTo4cp5XVHqFPmpyu9J65C1Yg==",
 			"cpu": [
 				"arm64"
 			],
@@ -150,13 +150,13 @@
 				"darwin"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/darwin-x64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/darwin-x64/-/darwin-x64-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/darwin-x64/-/darwin-x64-0.25.12.tgz",
+			"integrity": "sha512-HQ9ka4Kx21qHXwtlTUVbKJOAnmG1ipXhdWTmNXiPzPfWKpXqASVcWdnf2bnL73wgjNrFXAa3yYvBSd9pzfEIpA==",
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 				"x64"
 			],
@@ -167,13 +167,13 @@
 				"darwin"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/freebsd-arm64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/freebsd-arm64/-/freebsd-arm64-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/freebsd-arm64/-/freebsd-arm64-0.25.12.tgz",
+			"integrity": "sha512-gA0Bx759+7Jve03K1S0vkOu5Lg/85dou3EseOGUes8flVOGxbhDDh/iZaoek11Y8mtyKPGF3vP8XhnkDEAmzeg==",
 			"cpu": [
 				"arm64"
 			],
@@ -184,13 +184,13 @@
 				"freebsd"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/freebsd-x64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/freebsd-x64/-/freebsd-x64-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/freebsd-x64/-/freebsd-x64-0.25.12.tgz",
+			"integrity": "sha512-TGbO26Yw2xsHzxtbVFGEXBFH0FRAP7gtcPE7P5yP7wGy7cXK2oO7RyOhL5NLiqTlBh47XhmIUXuGciXEqYFfBQ==",
 			"cpu": [
 				"x64"
 			],
@@ -201,13 +201,13 @@
 				"freebsd"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/linux-arm": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/linux-arm/-/linux-arm-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/linux-arm/-/linux-arm-0.25.12.tgz",
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 				"arm"
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@@ -218,13 +218,13 @@
 				"linux"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/linux-arm64": {
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/linux-arm64/-/linux-arm64-0.25.12.tgz",
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 			"cpu": [
 				"arm64"
 			],
@@ -235,13 +235,13 @@
 				"linux"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/linux-ia32": {
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/linux-ia32/-/linux-ia32-0.25.12.tgz",
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 				"ia32"
 			],
@@ -252,13 +252,13 @@
 				"linux"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/linux-loong64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/linux-loong64/-/linux-loong64-0.21.5.tgz",
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/linux-loong64/-/linux-loong64-0.25.12.tgz",
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 			"cpu": [
 				"loong64"
 			],
@@ -269,13 +269,13 @@
 				"linux"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/linux-mips64el": {
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/linux-mips64el/-/linux-mips64el-0.25.12.tgz",
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@@ -286,13 +286,13 @@
 				"linux"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
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 		"node_modules/@esbuild/linux-ppc64": {
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@@ -303,13 +303,13 @@
 				"linux"
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 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
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 		"node_modules/@esbuild/linux-riscv64": {
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@@ -320,13 +320,13 @@
 				"linux"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
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 		},
 		"node_modules/@esbuild/linux-s390x": {
-			"version": "0.21.5",
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@@ -337,13 +337,13 @@
 				"linux"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
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+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/linux-x64/-/linux-x64-0.25.12.tgz",
+			"integrity": "sha512-uqZMTLr/zR/ed4jIGnwSLkaHmPjOjJvnm6TVVitAa08SLS9Z0VM8wIRx7gWbJB5/J54YuIMInDquWyYvQLZkgw==",
 			"cpu": [
 				"x64"
 			],
@@ -354,13 +354,30 @@
 				"linux"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
+			}
+		},
+		"node_modules/@esbuild/netbsd-arm64": {
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/netbsd-arm64/-/netbsd-arm64-0.25.12.tgz",
+			"integrity": "sha512-xXwcTq4GhRM7J9A8Gv5boanHhRa/Q9KLVmcyXHCTaM4wKfIpWkdXiMog/KsnxzJ0A1+nD+zoecuzqPmCRyBGjg==",
+			"cpu": [
+				"arm64"
+			],
+			"dev": true,
+			"license": "MIT",
+			"optional": true,
+			"os": [
+				"netbsd"
+			],
+			"engines": {
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/netbsd-x64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/netbsd-x64/-/netbsd-x64-0.21.5.tgz",
-			"integrity": "sha512-Woi2MXzXjMULccIwMnLciyZH4nCIMpWQAs049KEeMvOcNADVxo0UBIQPfSmxB3CWKedngg7sWZdLvLczpe0tLg==",
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/netbsd-x64/-/netbsd-x64-0.25.12.tgz",
+			"integrity": "sha512-Ld5pTlzPy3YwGec4OuHh1aCVCRvOXdH8DgRjfDy/oumVovmuSzWfnSJg+VtakB9Cm0gxNO9BzWkj6mtO1FMXkQ==",
 			"cpu": [
 				"x64"
 			],
@@ -371,13 +388,30 @@
 				"netbsd"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
+			}
+		},
+		"node_modules/@esbuild/openbsd-arm64": {
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/openbsd-arm64/-/openbsd-arm64-0.25.12.tgz",
+			"integrity": "sha512-fF96T6KsBo/pkQI950FARU9apGNTSlZGsv1jZBAlcLL1MLjLNIWPBkj5NlSz8aAzYKg+eNqknrUJ24QBybeR5A==",
+			"cpu": [
+				"arm64"
+			],
+			"dev": true,
+			"license": "MIT",
+			"optional": true,
+			"os": [
+				"openbsd"
+			],
+			"engines": {
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/openbsd-x64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/openbsd-x64/-/openbsd-x64-0.21.5.tgz",
-			"integrity": "sha512-HLNNw99xsvx12lFBUwoT8EVCsSvRNDVxNpjZ7bPn947b8gJPzeHWyNVhFsaerc0n3TsbOINvRP2byTZ5LKezow==",
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/openbsd-x64/-/openbsd-x64-0.25.12.tgz",
+			"integrity": "sha512-MZyXUkZHjQxUvzK7rN8DJ3SRmrVrke8ZyRusHlP+kuwqTcfWLyqMOE3sScPPyeIXN/mDJIfGXvcMqCgYKekoQw==",
 			"cpu": [
 				"x64"
 			],
@@ -388,13 +422,30 @@
 				"openbsd"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
+			}
+		},
+		"node_modules/@esbuild/openharmony-arm64": {
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/openharmony-arm64/-/openharmony-arm64-0.25.12.tgz",
+			"integrity": "sha512-rm0YWsqUSRrjncSXGA7Zv78Nbnw4XL6/dzr20cyrQf7ZmRcsovpcRBdhD43Nuk3y7XIoW2OxMVvwuRvk9XdASg==",
+			"cpu": [
+				"arm64"
+			],
+			"dev": true,
+			"license": "MIT",
+			"optional": true,
+			"os": [
+				"openharmony"
+			],
+			"engines": {
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/sunos-x64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/sunos-x64/-/sunos-x64-0.21.5.tgz",
-			"integrity": "sha512-6+gjmFpfy0BHU5Tpptkuh8+uw3mnrvgs+dSPQXQOv3ekbordwnzTVEb4qnIvQcYXq6gzkyTnoZ9dZG+D4garKg==",
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/sunos-x64/-/sunos-x64-0.25.12.tgz",
+			"integrity": "sha512-3wGSCDyuTHQUzt0nV7bocDy72r2lI33QL3gkDNGkod22EsYl04sMf0qLb8luNKTOmgF/eDEDP5BFNwoBKH441w==",
 			"cpu": [
 				"x64"
 			],
@@ -405,13 +456,13 @@
 				"sunos"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/win32-arm64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/win32-arm64/-/win32-arm64-0.21.5.tgz",
-			"integrity": "sha512-Z0gOTd75VvXqyq7nsl93zwahcTROgqvuAcYDUr+vOv8uHhNSKROyU961kgtCD1e95IqPKSQKH7tBTslnS3tA8A==",
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/win32-arm64/-/win32-arm64-0.25.12.tgz",
+			"integrity": "sha512-rMmLrur64A7+DKlnSuwqUdRKyd3UE7oPJZmnljqEptesKM8wx9J8gx5u0+9Pq0fQQW8vqeKebwNXdfOyP+8Bsg==",
 			"cpu": [
 				"arm64"
 			],
@@ -422,13 +473,13 @@
 				"win32"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/win32-ia32": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/win32-ia32/-/win32-ia32-0.21.5.tgz",
-			"integrity": "sha512-SWXFF1CL2RVNMaVs+BBClwtfZSvDgtL//G/smwAc5oVK/UPu2Gu9tIaRgFmYFFKrmg3SyAjSrElf0TiJ1v8fYA==",
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/win32-ia32/-/win32-ia32-0.25.12.tgz",
+			"integrity": "sha512-HkqnmmBoCbCwxUKKNPBixiWDGCpQGVsrQfJoVGYLPT41XWF8lHuE5N6WhVia2n4o5QK5M4tYr21827fNhi4byQ==",
 			"cpu": [
 				"ia32"
 			],
@@ -439,13 +490,13 @@
 				"win32"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@esbuild/win32-x64": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/@esbuild/win32-x64/-/win32-x64-0.21.5.tgz",
-			"integrity": "sha512-tQd/1efJuzPC6rCFwEvLtci/xNFcTZknmXs98FYDfGE4wP9ClFV98nyKrzJKVPMhdDnjzLhdUyMX4PsQAPjwIw==",
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/@esbuild/win32-x64/-/win32-x64-0.25.12.tgz",
+			"integrity": "sha512-alJC0uCZpTFrSL0CCDjcgleBXPnCrEAhTBILpeAp7M/OFgoqtAetfBzX0xM00MUsVVPpVjlPuMbREqnZCXaTnA==",
 			"cpu": [
 				"x64"
 			],
@@ -456,7 +507,7 @@
 				"win32"
 			],
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			}
 		},
 		"node_modules/@eslint-community/eslint-utils": {
@@ -3679,9 +3730,9 @@
 			"license": "MIT"
 		},
 		"node_modules/esbuild": {
-			"version": "0.21.5",
-			"resolved": "https://registry.npmjs.org/esbuild/-/esbuild-0.21.5.tgz",
-			"integrity": "sha512-mg3OPMV4hXywwpoDxu3Qda5xCKQi+vCTZq8S9J/EpkhB2HzKXq4SNFZE3+NK93JYxc8VMSep+lOUSC/RVKaBqw==",
+			"version": "0.25.12",
+			"resolved": "https://registry.npmjs.org/esbuild/-/esbuild-0.25.12.tgz",
+			"integrity": "sha512-bbPBYYrtZbkt6Os6FiTLCTFxvq4tt3JKall1vRwshA3fdVztsLAatFaZobhkBC8/BrPetoa0oksYoKXoG4ryJg==",
 			"dev": true,
 			"hasInstallScript": true,
 			"license": "MIT",
@@ -3689,32 +3740,35 @@
 				"esbuild": "bin/esbuild"
 			},
 			"engines": {
-				"node": ">=12"
+				"node": ">=18"
 			},
 			"optionalDependencies": {
-				"@esbuild/aix-ppc64": "0.21.5",
-				"@esbuild/android-arm": "0.21.5",
-				"@esbuild/android-arm64": "0.21.5",
-				"@esbuild/android-x64": "0.21.5",
-				"@esbuild/darwin-arm64": "0.21.5",
-				"@esbuild/darwin-x64": "0.21.5",
-				"@esbuild/freebsd-arm64": "0.21.5",
-				"@esbuild/freebsd-x64": "0.21.5",
-				"@esbuild/linux-arm": "0.21.5",
-				"@esbuild/linux-arm64": "0.21.5",
-				"@esbuild/linux-ia32": "0.21.5",
-				"@esbuild/linux-loong64": "0.21.5",
-				"@esbuild/linux-mips64el": "0.21.5",
-				"@esbuild/linux-ppc64": "0.21.5",
-				"@esbuild/linux-riscv64": "0.21.5",
-				"@esbuild/linux-s390x": "0.21.5",
-				"@esbuild/linux-x64": "0.21.5",
-				"@esbuild/netbsd-x64": "0.21.5",
-				"@esbuild/openbsd-x64": "0.21.5",
-				"@esbuild/sunos-x64": "0.21.5",
-				"@esbuild/win32-arm64": "0.21.5",
-				"@esbuild/win32-ia32": "0.21.5",
-				"@esbuild/win32-x64": "0.21.5"
+				"@esbuild/aix-ppc64": "0.25.12",
+				"@esbuild/android-arm": "0.25.12",
+				"@esbuild/android-arm64": "0.25.12",
+				"@esbuild/android-x64": "0.25.12",
+				"@esbuild/darwin-arm64": "0.25.12",
+				"@esbuild/darwin-x64": "0.25.12",
+				"@esbuild/freebsd-arm64": "0.25.12",
+				"@esbuild/freebsd-x64": "0.25.12",
+				"@esbuild/linux-arm": "0.25.12",
+				"@esbuild/linux-arm64": "0.25.12",
+				"@esbuild/linux-ia32": "0.25.12",
+				"@esbuild/linux-loong64": "0.25.12",
+				"@esbuild/linux-mips64el": "0.25.12",
+				"@esbuild/linux-ppc64": "0.25.12",
+				"@esbuild/linux-riscv64": "0.25.12",
+				"@esbuild/linux-s390x": "0.25.12",
+				"@esbuild/linux-x64": "0.25.12",
+				"@esbuild/netbsd-arm64": "0.25.12",
+				"@esbuild/netbsd-x64": "0.25.12",
+				"@esbuild/openbsd-arm64": "0.25.12",
+				"@esbuild/openbsd-x64": "0.25.12",
+				"@esbuild/openharmony-arm64": "0.25.12",
+				"@esbuild/sunos-x64": "0.25.12",
+				"@esbuild/win32-arm64": "0.25.12",
+				"@esbuild/win32-ia32": "0.25.12",
+				"@esbuild/win32-x64": "0.25.12"
 			}
 		},
 		"node_modules/escalade": {
@@ -4088,6 +4142,24 @@
 				"reusify": "^1.0.4"
 			}
 		},
+		"node_modules/fdir": {
+			"version": "6.5.0",
+			"resolved": "https://registry.npmjs.org/fdir/-/fdir-6.5.0.tgz",
+			"integrity": "sha512-tIbYtZbucOs0BRGqPJkshJUYdL+SDH7dVM8gjy+ERp3WAUjLEFJE+02kanyHtwjWOnwrKYBiwAmM0p4kLJAnXg==",
+			"dev": true,
+			"license": "MIT",
+			"engines": {
+				"node": ">=12.0.0"
+			},
+			"peerDependencies": {
+				"picomatch": "^3 || ^4"
+			},
+			"peerDependenciesMeta": {
+				"picomatch": {
+					"optional": true
+				}
+			}
+		},
 		"node_modules/file-entry-cache": {
 			"version": "6.0.1",
 			"resolved": "https://registry.npmjs.org/file-entry-cache/-/file-entry-cache-6.0.1.tgz",
@@ -7331,6 +7403,23 @@
 				"node": ">=0.8"
 			}
 		},
+		"node_modules/tinyglobby": {
+			"version": "0.2.15",
+			"resolved": "https://registry.npmjs.org/tinyglobby/-/tinyglobby-0.2.15.tgz",
+			"integrity": "sha512-j2Zq4NyQYG5XMST4cbs02Ak8iJUdxRM0XI5QyxXuZOzKOINmWurp3smXu3y5wDcJrptwpSjgXHzIQxR0omXljQ==",
+			"dev": true,
+			"license": "MIT",
+			"dependencies": {
+				"fdir": "^6.5.0",
+				"picomatch": "^4.0.3"
+			},
+			"engines": {
+				"node": ">=12.0.0"
+			},
+			"funding": {
+				"url": "https://github.com/sponsors/SuperchupuDev"
+			}
+		},
 		"node_modules/to-regex-range": {
 			"version": "5.0.1",
 			"resolved": "https://registry.npmjs.org/to-regex-range/-/to-regex-range-5.0.1.tgz",
@@ -7520,21 +7609,24 @@
 			"license": "MIT"
 		},
 		"node_modules/vite": {
-			"version": "5.4.21",
-			"resolved": "https://registry.npmjs.org/vite/-/vite-5.4.21.tgz",
-			"integrity": "sha512-o5a9xKjbtuhY6Bi5S3+HvbRERmouabWbyUcpXXUA1u+GNUKoROi9byOJ8M0nHbHYHkYICiMlqxkg1KkYmm25Sw==",
+			"version": "6.4.1",
+			"resolved": "https://registry.npmjs.org/vite/-/vite-6.4.1.tgz",
+			"integrity": "sha512-+Oxm7q9hDoLMyJOYfUYBuHQo+dkAloi33apOPP56pzj+vsdJDzr+j1NISE5pyaAuKL4A3UD34qd0lx5+kfKp2g==",
 			"dev": true,
 			"license": "MIT",
 			"dependencies": {
-				"esbuild": "^0.21.3",
-				"postcss": "^8.4.43",
-				"rollup": "^4.20.0"
+				"esbuild": "^0.25.0",
+				"fdir": "^6.4.4",
+				"picomatch": "^4.0.2",
+				"postcss": "^8.5.3",
+				"rollup": "^4.34.9",
+				"tinyglobby": "^0.2.13"
 			},
 			"bin": {
 				"vite": "bin/vite.js"
 			},
 			"engines": {
-				"node": "^18.0.0 || >=20.0.0"
+				"node": "^18.0.0 || ^20.0.0 || >=22.0.0"
 			},
 			"funding": {
 				"url": "https://github.com/vitejs/vite?sponsor=1"
@@ -7543,19 +7635,25 @@
 				"fsevents": "~2.3.3"
 			},
 			"peerDependencies": {
-				"@types/node": "^18.0.0 || >=20.0.0",
+				"@types/node": "^18.0.0 || ^20.0.0 || >=22.0.0",
+				"jiti": ">=1.21.0",
 				"less": "*",
 				"lightningcss": "^1.21.0",
 				"sass": "*",
 				"sass-embedded": "*",
 				"stylus": "*",
 				"sugarss": "*",
-				"terser": "^5.4.0"
+				"terser": "^5.16.0",
+				"tsx": "^4.8.1",
+				"yaml": "^2.4.2"
 			},
 			"peerDependenciesMeta": {
 				"@types/node": {
 					"optional": true
 				},
+				"jiti": {
+					"optional": true
+				},
 				"less": {
 					"optional": true
 				},
@@ -7576,6 +7674,12 @@
 				},
 				"terser": {
 					"optional": true
+				},
+				"tsx": {
+					"optional": true
+				},
+				"yaml": {
+					"optional": true
 				}
 			}
 		},
diff --git a/package.json b/package.json
index d680935..1bbd907 100644
--- a/package.json
+++ b/package.json
@@ -47,7 +47,7 @@
 		"tailwindcss": "^3.4.1",
 		"tslib": "^2.4.1",
 		"typescript": "^5.0.0",
-		"vite": "^5.4.21"
+		"vite": "^6.3.0"
 	},
 	"type": "module",
 	"dependencies": {
diff --git a/scripts/generate_kv_examples.py b/scripts/generate_kv_examples.py
new file mode 100644
index 0000000..e8ab1b4
--- /dev/null
+++ b/scripts/generate_kv_examples.py
@@ -0,0 +1,159 @@
+"""
+Generates KV cache example data for the kv-cache-explainer.
+Run: python scripts/generate_kv_examples.py
+Output: src/constants/examples/kv/ex{0..4}.js
+"""
+
+import torch
+import json
+import os
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+DECODE_STEPS = 5
+OUTPUT_DIR = "src/constants/examples/kv"
+
+PROMPTS = [
+    "Data visualization empowers users to",
+    "Artificial Intelligence is transforming the",
+    "As the spaceship was approaching the",
+    "On the deserted planet they discovered a",
+    "IEEE VIS conference highlights the",
+]
+
+def extract_head_vectors(past_key_values):
+    # Use layer 0 only for KV snapshot display
+    # New DynamicCache API: .layers[layer_idx].keys / .values shape [batch, heads, seq_len, head_dim]
+    if hasattr(past_key_values, 'layers'):
+        keys_all_heads = past_key_values.layers[0].keys[0]    # [12, seq_len, 64]
+        values_all_heads = past_key_values.layers[0].values[0]
+    elif hasattr(past_key_values, 'key_cache'):
+        keys_all_heads = past_key_values.key_cache[0][0]
+        values_all_heads = past_key_values.value_cache[0][0]
+    else:
+        keys_all_heads = past_key_values[0][0][0]   # [12, seq_len, 64]
+        values_all_heads = past_key_values[0][1][0]
+    return {
+        "keys": keys_all_heads.tolist(),    # [12, seq_len, 64]
+        "values": values_all_heads.tolist() # [12, seq_len, 64]
+    }
+
+def extract_attention_scores(attentions):
+    # attentions: tuple of [batch=1, num_heads=12, query_len, key_len] per layer
+    outputs = {}
+    for block_idx, layer_attn in enumerate(attentions):
+        for head_idx in range(12):
+            # Last token's attention row → shape [1, key_len]
+            scores = layer_attn[0, head_idx, -1, :].tolist()
+            key = f"block_{block_idx}_attn_head_{head_idx}_attn_dropout"
+            outputs[key] = {
+                "data": [scores],  # [[score0, score1, ...]] — 1×N
+                "dims": [1, len(scores)],
+                "size": len(scores)
+            }
+    return outputs
+
+def run_prefill(model, tokenizer, prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    token_ids = inputs["input_ids"][0].tolist()
+    tokens = [tokenizer.decode([tid]) for tid in token_ids]
+
+    with torch.no_grad():
+        output = model(**inputs, output_attentions=True, use_cache=True)
+
+    logits = output.logits[0, -1, :].tolist()
+    return {
+        "tokens": tokens,
+        "token_ids": token_ids,
+        "logits": logits,
+        "past_key_values": output.past_key_values,
+    }
+
+def extract_top_logits(logits_tensor, n=50):
+    """Return top-N [tokenId, logit] pairs sorted by logit descending."""
+    logits = logits_tensor.tolist()
+    indexed = sorted(enumerate(logits), key=lambda x: -x[1])[:n]
+    return [[int(i), round(v, 4)] for i, v in indexed]
+
+def run_decode_step(model, tokenizer, token_id, past_key_values):
+    input_ids = torch.tensor([[token_id]])
+    with torch.no_grad():
+        output = model(
+            input_ids=input_ids,
+            past_key_values=past_key_values,
+            output_attentions=True,
+            use_cache=True
+        )
+    next_token_id = int(output.logits[0, -1, :].argmax().item())
+    new_past = output.past_key_values
+    kv_snapshot = extract_head_vectors(new_past)
+    attention_outputs = extract_attention_scores(output.attentions)
+    top_logits = extract_top_logits(output.logits[0, -1, :])
+    return {
+        "input_token": tokenizer.decode([token_id]),
+        "input_token_id": token_id,
+        "next_token_id": next_token_id,
+        "top_logits": top_logits,
+        "kv_snapshot": kv_snapshot,
+        "attention_outputs": attention_outputs,
+        "past_key_values": new_past,
+    }
+
+def build_example(model, tokenizer, prompt):
+    print(f"  Prefill: {prompt!r}")
+    prefill = run_prefill(model, tokenizer, prompt)
+    first_token_id = int(torch.tensor(prefill["logits"]).argmax().item())
+    past = prefill["past_key_values"]
+    prompt_tokens = prefill["tokens"]
+
+    decode_steps = []
+    current_token_id = first_token_id
+
+    for step in range(DECODE_STEPS):
+        print(f"  Decode step {step + 1}: token_id={current_token_id} ({tokenizer.decode([current_token_id])!r})")
+        result = run_decode_step(model, tokenizer, current_token_id, past)
+        decode_steps.append({
+            "inputToken": result["input_token"],
+            "inputTokenId": result["input_token_id"],
+            "kvSnapshot": result["kv_snapshot"],
+            "attentionOutputs": result["attention_outputs"],
+            "topLogits": result["top_logits"],
+        })
+        past = result["past_key_values"]
+        current_token_id = result["next_token_id"]
+
+    return {
+        "promptTokens": prompt_tokens,
+        "decodeSteps": decode_steps,
+    }
+
+def write_js(example, var_name, path):
+    data_json = json.dumps(example, separators=(',', ':'))
+    js = f"export const {var_name} = {data_json};\n"
+    with open(path, "w") as f:
+        f.write(js)
+    size_kb = os.path.getsize(path) / 1024
+    print(f"  Written {path} ({size_kb:.1f} KB)")
+
+def main():
+    os.makedirs(OUTPUT_DIR, exist_ok=True)
+    print("Loading GPT-2...")
+    tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+    # eager required so output_attentions=True works during decode (past_key_values) steps
+    model = GPT2LMHeadModel.from_pretrained("gpt2", attn_implementation="eager")
+    model.eval()
+
+    for i, prompt in enumerate(PROMPTS):
+        print(f"\nExample {i}: {prompt!r}")
+        example = build_example(model, tokenizer, prompt)
+        write_js(example, f"kvEx{i}", os.path.join(OUTPUT_DIR, f"ex{i}.js"))
+
+    imports = "\n".join(f"import {{kvEx{i}}} from './ex{i}';" for i in range(5))
+    exports = ", ".join(f"kvEx{i}" for i in range(5))
+    index_js = f"{imports}\n\nexport {{ {exports} }};\n"
+    with open(os.path.join(OUTPUT_DIR, "index.js"), "w") as f:
+        f.write(index_js)
+    print(f"\nWritten {OUTPUT_DIR}/index.js")
+    print("\nDone.")
+
+if __name__ == "__main__":
+    main()
diff --git a/src/components/Attention.svelte b/src/components/Attention.svelte
index f87540f..5018a0b 100644
--- a/src/components/Attention.svelte
+++ b/src/components/Attention.svelte
@@ -161,7 +161,8 @@
 		}
 		&.expanded {
 			.title,
-			:global(.head-content) {
+			:global(.head-content),
+			:global(.multi-head .head-title) {
 				z-index: $EXPANDED_CONTENT_INDEX;
 			}
 			:global(.multi-head .head-card:first-child) {
diff --git a/src/components/AttentionMatrix.svelte b/src/components/AttentionMatrix.svelte
index 66bf244..3b03291 100644
--- a/src/components/AttentionMatrix.svelte
+++ b/src/components/AttentionMatrix.svelte
@@ -8,13 +8,16 @@
 		hoveredMatrixCell,
 		blockIdx,
 		isExpandOrCollapseRunning,
-		userId
+		userId,
+		headContentHeight
 	} from '~/store';
 	import classNames from 'classnames';
 	import Matrix from '~/components/common/Matrix.svelte';
 	import { gsap } from '~/utils/gsap';
 	import { maskArray } from '~/utils/array';
 	import { getContext, onMount } from 'svelte';
+	import { fly, fade } from 'svelte/transition';
+	import { cubicOut } from 'svelte/easing';
 	import resolveConfig from 'tailwindcss/resolveConfig';
 	import tailwindConfig from '../../tailwind.config';
 	import * as d3 from 'd3';
@@ -22,10 +25,13 @@
 	import { Tooltip } from 'flowbite-svelte';
 	import { ATTENTION_OUT } from '~/constants/opacity';
 	import { ga } from '~/utils/event';
-	import { ZoomInOutline } from 'flowbite-svelte-icons';
+	import { ZoomInOutline, CloseOutline } from 'flowbite-svelte-icons';
 	import TextbookTooltip from '~/components/common/TextbookTooltip.svelte';
 	import { textPages } from '~/utils/textbookPages';
 	import { highlightAttentionPath, removeAttentionPathHighlight } from '~/utils/textbook';
+	import { isDecoding, currentDecodeData, kvCache } from '~/store/kvcache';
+	import KVCacheTable from '~/components/KVCacheTable.svelte';
+	import VectorCanvas from '~/components/common/VectorCanvas.svelte';
 
 	const { theme } = resolveConfig(tailwindConfig);
 
@@ -42,6 +48,63 @@
 		$modelData?.outputs?.[`block_${$blockIdx}_attn_head_${$attentionHeadIdx}_attn_dropout`]?.data ||
 		placeHolderData;
 
+	// Decode mode: 1×N attention strip from currentDecodeData
+	$: decodeSoftmaxed =
+		$currentDecodeData?.attentionOutputs?.[
+			`block_${$blockIdx}_attn_head_${$attentionHeadIdx}_attn_dropout`
+		]?.data || [[]];
+
+	// Normalize to [0, max] so low-entropy distributions remain visible
+	$: decodeMax = Math.max(...(decodeSoftmaxed[0] ?? []), 0.01);
+	$: decodeColorScale = (d: number) =>
+		d3.interpolate('white', theme.colors['purple'][700])(d / decodeMax);
+
+	// Derive pre-softmax stages from softmax via log-space inversion
+	const EPS = 1e-9;
+	$: decodeScaled = [decodeSoftmaxed[0].map((p: number) => Math.log(p + EPS))];
+	$: decodeQK = [decodeSoftmaxed[0].map((p: number) => Math.log(p + EPS) * 8)]; // *sqrt(64)
+	$: decodeQKDomain = d3.extent(decodeQK[0].filter(Number.isFinite)) as [number, number];
+	$: decodeQKColorScale = (d: number) =>
+		d3.scaleLinear<string>().domain(decodeQKDomain).range(['white', theme.colors['purple'][700]])(d);
+	const decodeScaledColorScale = (d: number) =>
+		d3.scaleLinear<string>().domain([-3, 3]).range(['white', theme.colors['purple'][700]])(d);
+
+	// Compute attention output and normalize value vectors for display
+	$: {
+		const weights = decodeSoftmaxed[0];
+		const rawValues = $kvCache.map((e) => e.values[$attentionHeadIdx] ?? e.values[0] ?? []);
+
+		// Global min/max across all tokens + all dims for consistent color scale
+		const allNums = rawValues.flat().filter(Number.isFinite);
+		const vMin = allNums.length ? Math.min(...allNums) : -1;
+		const vMax = allNums.length ? Math.max(...allNums) : 1;
+		const vRange = vMax - vMin || 1;
+
+		// Normalize each token's value vector to [0, 1]
+		decodeValueNorm = rawValues.map((vec) => vec.map((v) => (v - vMin) / vRange));
+
+		// Compute out = attention @ values (raw), then normalize to [0, 1]
+		if (!weights.length || !rawValues.length) {
+			decodeOutValues = new Array(64).fill(0.5);
+		} else {
+			const out = new Array(64).fill(0);
+			for (let j = 0; j < 64; j++) {
+				for (let i = 0; i < weights.length; i++) {
+					out[j] += (weights[i] ?? 0) * (rawValues[i]?.[j] ?? 0);
+				}
+			}
+			const oMin = Math.min(...out);
+			const oMax = Math.max(...out);
+			const oRange = oMax - oMin || 1;
+			decodeOutValues = out.map((v) => (v - oMin) / oRange);
+		}
+	}
+
+	let decodeValueNorm: number[][] = [];
+	let decodeOutValues: number[] = new Array(64).fill(0.5);
+
+	let decodeOutOpen = false;
+
 	let factor = 1; //todo
 	let maxCellSize = 20 * factor;
 	let minCellSize = 10 * factor;
@@ -58,34 +121,46 @@
 	let attentionMatrixWidth = 0;
 
 	let isAttentionExpanded = false;
+	let decodeExpanded = false; // separate from prefill expand — no animation DOM deps
 
 	const blockId = getContext('block-id');
 
-	// event handling
-
-	$: if ($expandedBlock.id !== blockId && isAttentionExpanded) {
+	// event handling — only run prefill expand/collapse when NOT in decode mode
+	$: if ($expandedBlock.id !== blockId && isAttentionExpanded && !$isDecoding) {
 		isAttentionExpanded = false;
 		collapseAttention();
 	}
-	$: if ($expandedBlock.id === blockId && !isAttentionExpanded) {
+	$: if ($expandedBlock.id === blockId && !isAttentionExpanded && !$isDecoding) {
 		isAttentionExpanded = true;
 		expandAttention();
 	}
+	// When switching back to prefill, reset decode state
+	$: if (!$isDecoding) decodeExpanded = false;
+	$: if (!decodeExpanded) decodeOutOpen = false;
 
 	const onClickAttention = (e) => {
 		e.stopPropagation();
 		e.preventDefault();
 		textPages.find((page) => page.id === 'masked-self-attention')?.complete();
 
-		if (!isAttentionExpanded) {
+		if ($isDecoding) {
+			// Decode mode: toggle expand without running the prefill animation
+			decodeExpanded = !decodeExpanded;
+			expandedBlock.set({ id: decodeExpanded ? blockId : null });
+		} else if (!isAttentionExpanded) {
 			expandedBlock.set({ id: blockId });
 		}
 	};
 
 	let expandableEl: HTMLDivElement;
+	let decodeExpandableEl: HTMLDivElement;
 
 	function handleOutsideClick(e) {
-		if (isAttentionExpanded && !expandableEl.contains(e.target)) {
+		if (isAttentionExpanded && expandableEl && !expandableEl.contains(e.target)) {
+			expandedBlock.set({ id: null });
+		}
+		if (decodeExpanded && decodeExpandableEl && !decodeExpandableEl.contains(e.target)) {
+			decodeExpanded = false;
 			expandedBlock.set({ id: null });
 		}
 	}
@@ -317,6 +392,213 @@
 	};
 </script>
 
+{#if $isDecoding}
+	<div
+		class="decode-attention px-5"
+		class:expanded={decodeExpanded}
+		role="button"
+		tabindex="0"
+		bind:this={decodeExpandableEl}
+		on:click={onClickAttention}
+		on:keydown={onClickAttention}
+		style={`min-height: ${$headContentHeight}px`}
+	>
+		<!-- Collapsed: compact attention strip -->
+		{#if !decodeExpanded}
+			<div class="decode-collapsed" in:fade={{ duration: 250, easing: cubicOut }}>
+				{#if $currentDecodeData}
+					<div class="decode-labels">
+						<span class="label-kvcache">KV Cache</span>
+						<span class="label-new">New: {$currentDecodeData.inputToken}</span>
+					</div>
+				{/if}
+				<Matrix
+					data={decodeSoftmaxed}
+					showSize={false}
+					cellHeight={cellSize}
+					cellWidth={cellSize}
+					rowGap={3}
+					colGap={3}
+					shape={'circle'}
+					colorScale={decodeColorScale}
+					{onMouseOverCell}
+					{onMouseOutCell}
+					{showTooltip}
+				/>
+				<div class="matrix-label">
+					Attention <ZoomInOutline />
+				</div>
+			</div>
+		{:else}
+			<!-- Expanded: 3-panel attention pipeline + Out -->
+			<div
+				class="decode-expanded-inner"
+				role="none"
+				on:click|stopPropagation={() => {}}
+				in:fly={{ x: -24, duration: 400, easing: cubicOut }}
+				out:fade={{ duration: 150 }}
+			>
+				<!-- Step-by-step panels: Dot Product → Scaling·Mask → Softmax -->
+				<div class="decode-panels">
+					<!-- Dot Product -->
+					<div class="decode-panel">
+						<Matrix
+							data={decodeQK}
+							showSize={false}
+							cellHeight={cellSize}
+							cellWidth={cellSize}
+							rowGap={3}
+							colGap={3}
+							shape={'circle'}
+							colorScale={decodeQKColorScale}
+							{onMouseOverCell}
+							{onMouseOutCell}
+							{showTooltip}
+						/>
+						<div class="matrix-label">Dot product</div>
+						<div class="color-scale">
+							<span class="val">{decodeQKDomain[0]?.toFixed(1)}</span>
+							<div class="bar"></div>
+							<span class="val">{decodeQKDomain[1]?.toFixed(1)}</span>
+						</div>
+					</div>
+					<!-- Arrow -->
+					<svg class="panel-arrow" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="24" height="24" fill="none" viewBox="0 0 24 24">
+						<path stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M19 12H5m14 0-4 4m4-4-4-4"/>
+					</svg>
+					<!-- Scaling · Mask -->
+					<div class="decode-panel">
+						<Matrix
+							data={decodeScaled}
+							showSize={false}
+							cellHeight={cellSize}
+							cellWidth={cellSize}
+							rowGap={3}
+							colGap={3}
+							shape={'circle'}
+							colorScale={decodeScaledColorScale}
+							{onMouseOverCell}
+							{onMouseOutCell}
+							{showTooltip}
+						/>
+						<div class="matrix-label">Scaling · Mask</div>
+						<div class="color-scale">
+							<span class="val">-3.0</span>
+							<div class="bar"></div>
+							<span class="val">3.0</span>
+						</div>
+					</div>
+					<!-- Arrow -->
+					<svg class="panel-arrow" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="24" height="24" fill="none" viewBox="0 0 24 24">
+						<path stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M19 12H5m14 0-4 4m4-4-4-4"/>
+					</svg>
+					<!-- Softmax -->
+					<div class="decode-panel">
+						<Matrix
+							data={decodeSoftmaxed}
+							showSize={false}
+							cellHeight={cellSize}
+							cellWidth={cellSize}
+							rowGap={3}
+							colGap={3}
+							shape={'circle'}
+							colorScale={decodeColorScale}
+							{onMouseOverCell}
+							{onMouseOutCell}
+							{showTooltip}
+						/>
+						<div class="matrix-label">Softmax</div>
+						<div class="color-scale">
+							<span class="val">0.0</span>
+							<div class="bar"></div>
+							<span class="val">1.0</span>
+						</div>
+					</div>
+					<!-- Out trigger — styled like prefill Out column label -->
+					<div
+						class="decode-out-trigger"
+						role="button"
+						tabindex="0"
+						on:click|stopPropagation={() => (decodeOutOpen = !decodeOutOpen)}
+						on:keydown|stopPropagation={(e) => e.key === 'Enter' && (decodeOutOpen = !decodeOutOpen)}
+					>
+						<span class="out-label">Out</span>
+						<ZoomInOutline size="sm" />
+						<Tooltip class="popover" placement="bottom">click to see Attention Out calculation</Tooltip>
+					</div>
+				</div>
+
+				<!-- KV cache table -->
+				<KVCacheTable />
+
+				<!-- Inline Attention × Value = Out modal -->
+				{#if decodeOutOpen}
+					<div
+						class="decode-out-modal"
+						role="none"
+						on:click|stopPropagation={() => {}}
+						in:fly={{ y: 8, duration: 300, easing: cubicOut }}
+						out:fade={{ duration: 150 }}
+					>
+						<div class="decode-out-header">
+							<span>Attention Head {$attentionHeadIdx + 1} Out</span>
+							<button
+								class="decode-out-close"
+								on:click|stopPropagation={() => (decodeOutOpen = false)}
+							><CloseOutline class="h-4 w-4 text-gray-500" /></button>
+						</div>
+						<div class="decode-out-content">
+							<!-- Attention 1×N -->
+							<div class="out-col">
+								<div class="out-title">Attention</div>
+								<Matrix
+									data={decodeSoftmaxed}
+									showSize={false}
+									cellHeight={12}
+									cellWidth={12}
+									rowGap={3}
+									colGap={3}
+									shape={'circle'}
+									colorScale={decodeColorScale}
+								/>
+								<div class="out-size">(1, {decodeSoftmaxed[0].length})</div>
+							</div>
+							<span class="out-op">&times;</span>
+							<!-- Value: N token strips -->
+							<div class="out-col">
+								<div class="out-title">Value</div>
+								<div class="value-strips">
+									{#each decodeValueNorm as normVec}
+										<div class="vec-strip">
+											<VectorCanvas
+												data={normVec}
+												colorScale="green"
+												active={true}
+											/>
+										</div>
+									{/each}
+								</div>
+								<div class="out-size">({$kvCache.length}, 64)</div>
+							</div>
+							<span class="out-op">=</span>
+							<!-- Out: 1×64 -->
+							<div class="out-col">
+								<div class="out-title">Out</div>
+								<div class="vec-strip out-vec">
+									<VectorCanvas data={decodeOutValues} colorScale="purple" active={true} />
+								</div>
+								<div class="out-size">(1, 64)</div>
+							</div>
+						</div>
+						<div class="out-formula">
+							<Katex displayMode math={`\\sum_{k=1}^{${decodeSoftmaxed[0].length}} Attention_{1,k} \\cdot Value_{k,j} = Out_{1,j}`} />
+						</div>
+					</div>
+				{/if}
+			</div>
+		{/if}
+	</div>
+{:else}
 <div
 	class="flex items-center gap-8 px-5"
 	style={`--attention-matrix-width: ${attentionMatrixWidth}px;`}
@@ -528,8 +810,201 @@
 		</div>
 	</div>
 </div>
+{/if}
 
 <style lang="scss">
+	.decode-attention {
+		display: flex;
+		flex-direction: column;
+		gap: 0.5rem;
+		cursor: pointer;
+		border-radius: 0.5rem;
+		padding: 0.5rem;
+		transition: background-color 0.2s;
+		overflow: visible;
+
+		&:hover {
+			background-color: theme('colors.gray.50');
+		}
+
+		&.expanded {
+			background-color: transparent;
+			overflow: visible;
+		}
+
+		.decode-collapsed {
+			display: flex;
+			flex-direction: column;
+			align-items: flex-start;
+			gap: 0.25rem;
+		}
+
+		.decode-labels {
+			display: flex;
+			justify-content: space-between;
+			width: 100%;
+			font-size: 0.7rem;
+			color: theme('colors.gray.400');
+		}
+
+		.label-new {
+			color: theme('colors.blue.400');
+			font-weight: 500;
+		}
+
+		.matrix-label {
+			color: theme('colors.gray.400');
+			font-size: 0.8rem;
+			white-space: nowrap;
+			display: flex;
+			align-items: center;
+			gap: 0.25rem;
+		}
+
+		.decode-expanded-inner {
+			display: flex;
+			flex-direction: column;
+			gap: 1rem;
+			cursor: default;
+			overflow: visible;
+		}
+
+		.decode-panels {
+			display: flex;
+			flex-direction: row;
+			align-items: center;
+			gap: 0.5rem;
+			flex-wrap: nowrap;
+			overflow: visible;
+
+			.decode-panel {
+				display: flex;
+				flex-direction: column;
+				align-items: flex-start;
+				gap: 0.25rem;
+				position: relative;
+				padding-bottom: 1.5rem;
+				flex-shrink: 0;
+			}
+
+			.panel-arrow {
+				color: theme('colors.gray.300');
+				flex-shrink: 0;
+			}
+		}
+
+		.decode-out-trigger {
+			cursor: pointer;
+			color: theme('colors.purple.400');
+			display: flex;
+			flex-direction: column;
+			align-items: center;
+			gap: 0.2rem;
+			padding: 0.25rem 0.5rem;
+			flex-shrink: 0;
+			transition: color 0.15s;
+			align-self: flex-start;
+
+			.out-label {
+				font-size: 0.9rem;
+				font-weight: 500;
+				white-space: nowrap;
+			}
+
+			&:hover {
+				color: theme('colors.purple.600');
+			}
+		}
+
+		.decode-out-modal {
+			background: white;
+			border: 1px solid theme('colors.gray.200');
+			border-radius: 0.5rem;
+			padding: 1rem 1.5rem 0.75rem;
+			box-shadow: 0 2px 8px rgba(0, 0, 0, 0.06);
+
+			.decode-out-header {
+				display: flex;
+				justify-content: space-between;
+				align-items: center;
+				font-weight: 600;
+				font-size: 0.85rem;
+				color: theme('colors.gray.800');
+				margin-bottom: 1rem;
+			}
+
+			.decode-out-close {
+				background: none;
+				border: none;
+				cursor: pointer;
+				padding: 0.1rem;
+				display: flex;
+				align-items: center;
+			}
+
+			.decode-out-content {
+				display: flex;
+				align-items: flex-start;
+				gap: 1rem;
+			}
+
+			.out-col {
+				display: flex;
+				flex-direction: column;
+				align-items: center;
+				gap: 0.4rem;
+				position: relative;
+
+				.out-title {
+					font-size: 0.75rem;
+					color: theme('colors.gray.700');
+					font-weight: 500;
+					white-space: nowrap;
+				}
+
+				.out-size {
+					font-size: 0.7rem;
+					color: theme('colors.gray.400');
+					font-family: monospace;
+					margin-top: 0.25rem;
+				}
+			}
+
+			.out-op {
+				font-size: 1.2rem;
+				color: theme('colors.gray.700');
+				align-self: center;
+				margin-top: 1.2rem;
+			}
+
+			.value-strips {
+				display: flex;
+				flex-direction: column;
+				gap: 2px;
+			}
+
+			.vec-strip {
+				position: relative;
+				width: 24px;
+				height: 32px;
+				flex-shrink: 0;
+			}
+
+			.out-vec {
+				height: 64px;
+			}
+
+			.out-formula {
+				margin-top: 0.75rem;
+				text-align: center;
+				:global(.katex-display) {
+					margin: 0 !important;
+					font-size: 0.85rem;
+				}
+			}
+		}
+	}
+
 	.attention-matrix-container {
 		cursor: pointer;
 		border-radius: 0.5rem;
diff --git a/src/components/InputForm.svelte b/src/components/InputForm.svelte
index 63b5b90..c7f3216 100644
--- a/src/components/InputForm.svelte
+++ b/src/components/InputForm.svelte
@@ -27,6 +27,14 @@
 	import Sampling from './Sampling.svelte';
 	import { completeCurrentAnimation } from '~/utils/animation';
 	import { textPages } from '~/utils/textbookPages';
+	import { afterUpdate } from 'svelte';
+
+	afterUpdate(() => {
+		// Sync contenteditable DOM when the store updates programmatically (e.g. during KV decode)
+		if (inputRef && document.activeElement !== inputRef) {
+			inputRef.innerText = inputTextTemp;
+		}
+	});
 
 	let inputRef: HTMLDivElement;
 	let predictRef: HTMLDivElement;
diff --git a/src/components/KVCacheTable.svelte b/src/components/KVCacheTable.svelte
new file mode 100644
index 0000000..ec849eb
--- /dev/null
+++ b/src/components/KVCacheTable.svelte
@@ -0,0 +1,139 @@
+<script lang="ts">
+	import { kvCache, promptTokenCount } from '~/store/kvcache';
+	import { attentionHeadIdx } from '~/store';
+	import VectorCanvas from '~/components/common/VectorCanvas.svelte';
+	import { afterUpdate } from 'svelte';
+	import { gsap } from '~/utils/gsap';
+
+	let prevLength = 0;
+	let colEls: (HTMLElement | null)[] = [];
+
+	afterUpdate(() => {
+		const currentLength = $kvCache.length;
+		if (currentLength > prevLength) {
+			const newCol = colEls[currentLength - 1];
+			if (newCol) {
+				gsap.from(newCol, { opacity: 0, x: 6, duration: 0.35, ease: 'power2.out' });
+			}
+		}
+		prevLength = currentLength;
+	});
+</script>
+
+{#if $kvCache.length > 0}
+	<div class="kv-table">
+		<!-- Row labels: K / V -->
+		<div class="row-labels">
+			<span class="row-spacer"></span>
+			<span class="row-label k-label">K</span>
+			<span class="row-label v-label">V</span>
+		</div>
+		<!-- One column per cached token -->
+		<div class="kv-cols-wrap">
+			{#each $kvCache as entry, i}
+				<div
+					class="kv-col"
+					class:is-prompt={i < $promptTokenCount}
+					bind:this={colEls[i]}
+				>
+					<span class="token-label" title={entry.token}>{entry.token}</span>
+					<div class="col-vec-container">
+						<VectorCanvas
+							data={entry.keys[$attentionHeadIdx] ?? entry.keys[0] ?? []}
+							colorScale="red"
+							active={true}
+						/>
+					</div>
+					<div class="col-vec-container">
+						<VectorCanvas
+							data={entry.values[$attentionHeadIdx] ?? entry.values[0] ?? []}
+							colorScale="green"
+							active={true}
+						/>
+					</div>
+				</div>
+			{/each}
+		</div>
+	</div>
+{/if}
+
+<style lang="scss">
+	.kv-table {
+		display: flex;
+		flex-direction: row;
+		align-items: flex-start;
+		gap: 3px;
+		font-size: 0.7rem;
+		overflow-x: auto;
+		padding-bottom: 2px;
+	}
+
+	/* Left-side row labels: K / V */
+	.row-labels {
+		display: flex;
+		flex-direction: column;
+		align-items: center;
+		flex-shrink: 0;
+		gap: 2px;
+
+		.row-spacer {
+			/* matches token-label height */
+			height: 2rem;
+		}
+
+		.row-label {
+			height: 48px;
+			display: flex;
+			align-items: center;
+			font-weight: 600;
+			font-size: 0.7rem;
+		}
+
+		.k-label {
+			color: theme('colors.red.500');
+		}
+
+		.v-label {
+			color: theme('colors.green.600');
+		}
+	}
+
+	/* Scrollable column strip */
+	.kv-cols-wrap {
+		display: flex;
+		flex-direction: row;
+		gap: 3px;
+		overflow-x: auto;
+	}
+
+	/* One column per token */
+	.kv-col {
+		display: flex;
+		flex-direction: column;
+		align-items: center;
+		gap: 2px;
+		flex-shrink: 0;
+
+		.token-label {
+			writing-mode: vertical-lr;
+			transform: rotate(180deg);
+			height: 2rem;
+			font-size: 0.65rem;
+			color: theme('colors.gray.600');
+			white-space: nowrap;
+			overflow: hidden;
+			text-overflow: ellipsis;
+		}
+
+		&.is-prompt .token-label {
+			color: theme('colors.gray.400');
+		}
+	}
+
+	.col-vec-container {
+		position: relative;
+		width: 24px;
+		height: 48px;
+		flex-shrink: 0;
+	}
+</style>
diff --git a/src/components/textbook/Textbook.svelte b/src/components/textbook/Textbook.svelte
index be56fbe..84b89f1 100644
--- a/src/components/textbook/Textbook.svelte
+++ b/src/components/textbook/Textbook.svelte
@@ -510,6 +510,27 @@
 		background: var(--textbook-highlight-background) !important;
 	}
 
+	// kv-cache pages
+	:global(.decode-controls.textbook-highlight) {
+		box-shadow: var(--textbook-highlight-shadow-out) !important;
+		border-color: var(--textbook-highlight-color) !important;
+		position: relative;
+
+		&::after {
+			content: '👆';
+			display: block;
+			white-space: nowrap;
+			position: absolute;
+			bottom: -2.5rem;
+			left: 50%;
+			transform: translateX(-50%);
+			color: var(--textbook-highlight-color);
+			font-size: 2rem;
+			pointer-events: none;
+			animation: finger-poke 1.5s ease-in-out infinite;
+		}
+	}
+
 	// animation
 	@keyframes finger-poke {
 		0%,
diff --git a/src/components/textbook/TextbookCard.svelte b/src/components/textbook/TextbookCard.svelte
index e69bdf4..91bfe06 100644
--- a/src/components/textbook/TextbookCard.svelte
+++ b/src/components/textbook/TextbookCard.svelte
@@ -452,4 +452,57 @@
 		flex: 1;
 		line-height: 1.4;
 	}
+
+	/* Image and citation styles */
+	:global(.textbook-content .tb-figure) {
+		margin: 0.5rem 0;
+		text-align: center;
+	}
+
+	:global(.textbook-content .tb-img) {
+		max-width: 100%;
+		max-height: 140px;
+		width: auto;
+		height: auto;
+		object-fit: contain;
+		border-radius: 4px;
+		border: 1px solid theme('colors.gray.200');
+	}
+
+	:global(.textbook-content figcaption) {
+		font-size: 0.75rem;
+		color: theme('colors.gray.500');
+		margin-top: 0.2rem;
+		font-style: italic;
+		line-height: 1.3;
+	}
+
+	:global(.textbook-content .tb-citation) {
+		font-size: 0.75rem;
+		color: theme('colors.gray.500');
+		border-top: 1px solid theme('colors.gray.100');
+		padding-top: 0.35rem;
+		margin-top: 0.4rem;
+	}
+
+	:global(.textbook-content .tb-cite-link) {
+		color: var(--textbook-highlight-color);
+		text-decoration: underline;
+		text-underline-offset: 2px;
+	}
+
+	:global(.textbook-content code) {
+		font-family: ui-monospace, monospace;
+		font-size: 0.8rem;
+		background: theme('colors.gray.100');
+		padding: 0.1rem 0.3rem;
+		border-radius: 3px;
+		color: theme('colors.gray.700');
+	}
+
+	/* Scrollable content area */
+	:global(.carousel-slide .textbook-content) {
+		height: 100%;
+		overflow-y: auto;
+	}
 </style>
diff --git a/src/constants/examples/kv/ex0.js b/src/constants/examples/kv/ex0.js
new file mode 100644
index 0000000..46efb30
--- /dev/null
+++ b/src/constants/examples/kv/ex0.js
@@ -0,0 +1 @@
+export const kvEx0 = {"promptTokens":["Data"," visualization"," em","powers"," users"," to"],"decodeSteps":[{"inputToken":" visualize","inputTokenId":38350,"kvSnapshot":{"keys":[[[-1.3581807613372803,2.795064687728882,0.7305971384048462,-0.730095624923706,0.7611039280891418,0.7685757279396057,0.2989909052848816,0.47570377588272095,-1.4931352138519287,0.8233999013900757,-0.18174321949481964,-0.10247163474559784,0.20720699429512024,-0.3886682689189911,-0.1702272891998291,-0.47078031301498413,0.8918800950050354,0.10596220195293427,2.185938835144043,0.31488269567489624,-1.5604302883148193,0.028916381299495697,-0.48737233877182007,-1.2104825973510742,-0.2328943908214569,-0.13651706278324127,-0.3613066077232361,-0.6699439883232117,0.007654955144971609,1.3627352714538574,0.8075047731399536,-1.831930160522461,-0.986684262752533,-0.30123645067214966,0.12374269962310791,-0.3688659071922302,1.2609199285507202,0.6132920384407043,-0.6617754101753235,0.8482213020324707,-0.8366281390190125,0.6200211644172668,-0.23667465150356293,0.48572710156440735,-0.3668454885482788,-0.933896005153656,0.2702696621417999,0.20324626564979553,-1.4445619583129883,0.8910866379737854,0.5828569531440735,-0.5366001725196838,1.0247427225112915,1.1746184825897217,-0.26609015464782715,0.6412935853004456,0.0391753725707531,-1.1370705366134644,0.979632556438446,0.15984447300434113,-0.4284294843673706,-0.43629777431488037,-0.700202226638794,1.40861976146698],[-2.1876399517059326,2.2153537273406982,1.2106444835662842,0.07120577991008759,0.9717149138450623,0.04311934486031532,0.1362287700176239,0.5144205689430237,-0.7722027897834778,-0.6221519708633423,0.02017829567193985,-0.17351870238780975,0.6450661420822144,-0.6298307180404663,-1.540457844734192,0.1855778992176056,0.7244887351989746,-0.7952651381492615,0.8725098371505737,-0.7863655090332031,-2.4437406063079834,-0.9923844337463379,0.6916458010673523,-0.9346216320991516,-0.5866991877555847,0.5867804884910583,0.08497519046068192,-0.6322430968284607,-2.238218307495117,0.17472721636295319,1.214175820350647,-2.2861218452453613,-0.9501372575759888,0.9495582580566406,1.0189952850341797,-1.77424955368042,1.693957805633545,0.0859682708978653,0.8577398061752319,1.028236746788025,0.04708892107009888,2.59216570854187,-0.07275521755218506,1.4419643878936768,-1.2624047994613647,-1.0393186807632446,0.06682375073432922,-1.6542465686798096,-0.6928178668022156,0.6274548768997192,0.11539652198553085,0.6468584537506104,1.9393318891525269,2.269890785217285,0.980487585067749,1.2085739374160767,0.1846126765012741,-1.8759617805480957,0.2739720642566681,-0.22154894471168518,1.051684856414795,0.023716626688838005,-1.9445546865463257,1.8813821077346802],[-1.8512252569198608,2.3679299354553223,1.0294135808944702,1.1509058475494385,1.917678952217102,-0.269195020198822,1.2459521293640137,0.0882779136300087,-1.9790377616882324,-0.22373773157596588,-0.33998775482177734,1.4500120878219604,0.654741108417511,-0.38491004705429077,-1.3222146034240723,1.304543137550354,-0.18664267659187317,-1.1763858795166016,0.5672171115875244,-0.656747043132782,-1.0567927360534668,-1.6970444917678833,-1.0538839101791382,-1.1814640760421753,1.4816546440124512,0.9990062117576599,-1.5337631702423096,-0.8942440152168274,-0.3625677525997162,-0.024027597159147263,-0.019825439900159836,-0.7142062187194824,-3.2201504707336426,0.5666472315788269,1.4020335674285889,-0.3417264521121979,-0.12236044555902481,0.897095263004303,0.7130146026611328,0.7382202744483948,1.9334895610809326,0.8080770969390869,1.554296612739563,0.8343871831893921,-1.2721575498580933,-0.4934678077697754,-0.3307827115058899,0.420968234539032,0.22665244340896606,2.1965079307556152,1.783894658088684,-1.7053321599960327,2.239788770675659,0.5178685784339905,-0.3777533769607544,3.001129150390625,-0.36468538641929626,-0.4206928312778473,0.4318559765815735,1.3116909265518188,-0.871592104434967,-2.0837669372558594,-1.594586730003357,2.235973834991455],[-1.9662834405899048,1.9458268880844116,2.740351676940918,1.1403961181640625,1.3229790925979614,0.7743180990219116,0.6216492652893066,0.7595449686050415,-1.2727960348129272,1.5972490310668945,1.5522452592849731,-0.16855140030384064,-0.7272548079490662,0.529434859752655,-0.3657589852809906,0.7507185339927673,-0.04688543453812599,-0.608004629611969,0.9258695840835571,-0.7817185521125793,-2.260531425476074,-0.9546788930892944,-0.7592415809631348,-0.8499056100845337,0.5103492140769958,0.23709803819656372,-0.47059211134910583,0.9479073286056519,-0.16020190715789795,-0.6037483215332031,1.5500354766845703,-0.30720606446266174,-1.8575540781021118,0.9139820337295532,0.7958326935768127,1.0146054029464722,0.17284785211086273,1.332510232925415,-1.089304804801941,0.16020509600639343,0.8651347160339355,2.326244592666626,-0.5672352313995361,1.2717533111572266,1.8120627403259277,-0.972652792930603,0.482776015996933,-1.6079717874526978,-0.5207825899124146,0.595230221748352,1.0498955249786377,-1.250575304031372,1.0274842977523804,-0.21239922940731049,-0.8355131149291992,0.6894433498382568,0.24023275077342987,0.9028703570365906,0.07557778805494308,0.8670297861099243,-1.6650235652923584,-0.1612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diff --git a/src/constants/examples/kv/ex1.js b/src/constants/examples/kv/ex1.js
new file mode 100644
index 0000000..de7c476
--- /dev/null
+++ b/src/constants/examples/kv/ex1.js
@@ -0,0 +1 @@
+export const kvEx1 = {"promptTokens":["Art","ificial"," Intelligence"," is"," transforming"," the"],"decodeSteps":[{"inputToken":" way","inputTokenId":835,"kvSnapshot":{"keys":[[[-1.7865630388259888,2.2443268299102783,0.6659530401229858,0.37259864807128906,0.8252699971199036,0.10881554335355759,-0.1348385214805603,0.19554433226585388,-1.6327563524246216,-0.21361269056797028,0.29715695977211,-1.3086422681808472,1.139228105545044,0.7486146092414856,-2.2277605533599854,-0.09999760240316391,0.17119617760181427,0.46710875630378723,1.976853370666504,-0.007480056490749121,-1.0222457647323608,-1.1451975107192993,0.37531980872154236,-1.4899475574493408,0.12337169051170349,-0.8964917063713074,-0.26292479038238525,-0.7362614274024963,-1.107954502105713,-0.3729386031627655,0.923655092716217,-0.3955325782299042,-0.4610389471054077,0.4002404510974884,-0.19541041553020477,0.42490631341934204,0.9896157383918762,0.423511266708374,-0.7821966409683228,1.060056209564209,-1.0000168085098267,0.5259507298469543,-1.2139511108398438,0.7356908321380615,-0.8808957934379578,-1.1651262044906616,0.8233994841575623,-0.9651850461959839,-0.6810148358345032,0.647753894329071,0.5674626231193542,-0.37078067660331726,0.8400692939758301,-0.15519289672374725,-0.16316312551498413,1.759415864944458,-0.3136717975139618,-0.5029412508010864,0.4395322799682617,0.7634404897689819,-0.0725058764219284,-0.24612924456596375,-1.3192940950393677,2.118468999862671],[-1.7611318826675415,2.894418239593506,1.435683250427246,0.636173665523529,0.43288272619247437,1.5745234489440918,0.3494434952735901,-0.2550230026245117,-1.662125825881958,0.5770795345306396,1.7569975852966309,1.211918592453003,1.1023746728897095,-0.5880908966064453,-0.7048806548118591,-0.1555982083082199,0.5309944152832031,0.4162365198135376,1.7431784868240356,-0.2682909667491913,-2.5048563480377197,1.2402539253234863,-0.7032581567764282,-2.5462443828582764,0.5644168257713318,-0.10145693272352219,-1.3515335321426392,-0.7077292799949646,-0.8685686588287354,-0.7932013273239136,1.7926304340362549,-0.7117632627487183,-2.4825429916381836,1.4285271167755127,1.3713737726211548,0.2169867902994156,0.6086282730102539,1.4140807390213013,0.7671580910682678,-0.15565793216228485,-0.8223119974136353,0.8939053416252136,1.7325187921524048,0.5031636953353882,0.3971908986568451,-0.3468794524669647,-1.3790628910064697,-1.4650955200195312,-2.529650926589966,1.2293635606765747,0.8867951035499573,-0.211131289601326,1.360535979270935,1.7666465044021606,0.3547702133655548,1.7779831886291504,-0.5207821726799011,0.94114089012146,0.8634307384490967,-1.0816775560379028,-1.8067901134490967,-1.1191877126693726,-1.1676266193389893,1.3559324741363525],[-2.7521097660064697,3.606260061264038,0.20546801388263702,0.2938125431537628,1.023585319519043,1.532138466835022,1.0006837844848633,0.7836170196533203,-3.410017728805542,-0.5755853652954102,1.4875380992889404,-0.6805141568183899,0.2079300731420517,-0.9287107586860657,-0.6258038282394409,0.6517295837402344,1.5008089542388916,-1.5414113998413086,0.6111862659454346,-0.6295812129974365,-3.024782657623291,-1.241899847984314,0.21003080904483795,-0.22813956439495087,-0.766392707824707,-0.20651695132255554,-1.5709542036056519,0.24335554242134094,-0.5485687851905823,1.973399043083191,-0.14428426325321198,-1.1325008869171143,-1.7128580808639526,1.0525259971618652,0.8651678562164307,-0.9939107894897461,1.2185578346252441,0.8783248662948608,-0.08291376382112503,-1.0196952819824219,0.5986623764038086,0.80494624376297,-0.8234806656837463,1.1531461477279663,1.0556960105895996,-1.1023720502853394,-1.0757243633270264,-2.4583842754364014,-0.2585485279560089,1.3491368293762207,0.9811385273933411,-1.1234254837036133,1.1668063402175903,2.1482529640197754,1.4431285858154297,2.2442376613616943,2.641695022583008,0.1049138680100441,0.4646739959716797,1.8687719106674194,-0.33692845702171326,1.0448451042175293,-0.5470543503761292,3.047424077987671],[-1.9828113317489624,2.4026007652282715,2.0973916053771973,0.1577707976102829,1.5808312892913818,-0.18707014620304108,1.6808762550354004,-0.13863013684749603,-1.5430206060409546,0.8054895997047424,0.8844834566116333,0.32969504594802856,0.7433069348335266,0.12108053267002106,0.36855989694595337,-0.10709614306688309,0.7724081873893738,-0.7322842478752136,3.0140981674194336,-0.06187206879258156,-2.7541327476501465,0.022920435294508934,0.13628193736076355,-1.7917771339416504,0.5645221471786499,0.5954244136810303,1.0822498798370361,0.6670658588409424,-0.6560441851615906,-0.009749343618750572,-2.582225799560547,-1.0604218244552612,-2.7202773094177246,1.1779402494430542,1.7040475606918335,-0.6719681024551392,0.9957143068313599,1.3674547672271729,0.6432778835296631,1.264407992362976,-0.4029327630996704,0.9751947522163391,-0.5225459337234497,1.9398146867752075,-0.7438803911209106,0.3668665885925293,1.4571399688720703,-1.4238226413726807,-0.13372889161109924,1.8673144578933716,1.2632441520690918,-1.3894493579864502,1.6452666521072388,0.3476659655570984,-0.2250177413225174,2.351799726486206,1.394308090209961,0.3580406606197357,1.2836323976516724,1.2834362983703613,-1.3449808359146118,-1.5629528760910034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diff --git a/src/constants/examples/kv/ex2.js b/src/constants/examples/kv/ex2.js
new file mode 100644
index 0000000..aa5b754
--- /dev/null
+++ b/src/constants/examples/kv/ex2.js
@@ -0,0 +1 @@
+export const kvEx2 = {"promptTokens":["As"," the"," spaceship"," was"," approaching"," the"],"decodeSteps":[{"inputToken":" planet","inputTokenId":5440,"kvSnapshot":{"keys":[[[-0.9792780876159668,1.802293062210083,0.9218435883522034,0.021011734381318092,0.6753074526786804,0.38926202058792114,0.22319717705249786,0.48307639360427856,-1.6441251039505005,0.2699263095855713,-0.2822515368461609,-0.27664852142333984,0.7594154477119446,0.13589245080947876,-0.9602063894271851,0.2036416083574295,0.37189406156539917,0.05159574747085571,2.090014696121216,0.27892449498176575,-1.6865917444229126,0.43798235058784485,-0.9356207251548767,-0.983555018901825,-0.09369268268346786,-0.5880059599876404,-0.5811841487884521,0.07576671987771988,-0.3070141673088074,-0.3118131160736084,0.6095665097236633,-0.811484694480896,-0.865529477596283,0.0548403300344944,-0.36952224373817444,0.05400289595127106,0.8244267702102661,0.4421946108341217,-0.2650352418422699,0.6469272971153259,-0.18232473731040955,0.5466623306274414,-0.22992829978466034,0.3969293534755707,-1.0449377298355103,-0.12263285368680954,1.0065022706985474,-0.07425687462091446,-0.026422906666994095,0.15643341839313507,0.6323541402816772,-1.1915231943130493,0.9604327082633972,0.32403552532196045,-0.05615101382136345,1.2140530347824097,0.1845378577709198,-0.5879786610603333,0.12112420797348022,0.2672991156578064,-0.628606379032135,-0.9380122423171997,-0.6522179245948792,1.2440464496612549],[-2.1015217304229736,2.69938588142395,1.720770239830017,0.06735403090715408,0.8563122153282166,0.507075309753418,0.5672464370727539,1.1351993083953857,-1.2756800651550293,1.0221080780029297,0.2478073239326477,0.9594515562057495,0.9112045764923096,0.0824609324336052,-1.3140476942062378,0.31746968626976013,-0.3076125383377075,-0.8064106702804565,2.382298469543457,0.6058070063591003,-2.9994657039642334,-0.8779362440109253,-0.6245948672294617,-1.232234001159668,-0.4650470018386841,0.3021223545074463,0.4573853313922882,0.08058059960603714,-0.26976853609085083,-0.3799256384372711,-1.6703431606292725,-0.7535884380340576,-1.5860121250152588,0.994138240814209,1.150132179260254,-0.12368791550397873,1.1407878398895264,1.1367337703704834,0.4640786051750183,0.11501576006412506,-0.5172367095947266,1.4128422737121582,-0.19445087015628815,1.1393758058547974,-0.910517156124115,-0.7142145037651062,0.7643955945968628,-0.3221496343612671,-1.6533739566802979,1.1148067712783813,0.7537150979042053,-1.1314157247543335,1.9118022918701172,0.7717965245246887,0.14899612963199615,2.5224146842956543,-0.013426600024104118,-0.21717041730880737,0.5551036596298218,1.8830153942108154,-1.555271863937378,-0.6648080945014954,-1.276104211807251,1.9811099767684937],[-2.150646209716797,2.7629165649414062,0.5541613101959229,0.20025940239429474,1.9213091135025024,0.3947066068649292,1.6267964839935303,-0.7185736894607544,-1.2344614267349243,2.090137481689453,1.236032247543335,0.9057238698005676,-0.1876675933599472,-0.7090065479278564,-1.7029789686203003,0.9370442032814026,1.3647297620773315,-1.430067539215088,0.4208778738975525,-1.649399757385254,-0.6826906204223633,-0.4906342625617981,0.5533833503723145,-1.1534305810928345,1.48128080368042,-0.9587857723236084,0.040100473910570145,-0.2689710557460785,0.1418992578983307,-1.2170095443725586,0.2855270802974701,-1.6315191984176636,-1.2965118885040283,0.5485242605209351,-0.2877969741821289,0.756572425365448,2.5713613033294678,1.8100720643997192,2.306779384613037,-1.5641018152236938,-0.3000279366970062,2.441182851791382,1.2054206132888794,1.873076319694519,-0.2127666175365448,-1.594261884689331,0.8734412789344788,-0.6509082913398743,1.3306293487548828,2.3122570514678955,0.6978408694267273,-1.6168577671051025,0.8627001643180847,2.458418607711792,1.3094687461853027,1.1782773733139038,-0.8128236532211304,0.4177025258541107,-0.022925427183508873,-0.5175896286964417,-0.8587644696235657,-0.6169637441635132,-1.7001718282699585,1.1232762336730957],[-1.893315315246582,2.176283121109009,2.1788883209228516,0.07341612875461578,2.221766471862793,-0.054888464510440826,1.2927123308181763,-0.1945524662733078,-1.120406985282898,1.0615897178649902,0.8553295135498047,0.6975743770599365,0.18173082172870636,0.5357698798179626,0.08602271974086761,-0.31829747557640076,0.935844361782074,-0.9607031941413879,2.7720603942871094,-0.24008087813854218,-2.226032018661499,0.4801856577396393,0.8467481136322021,-1.3983070850372314,0.8928723931312561,0.6101342439651489,1.3257312774658203,0.8092056512832642,-0.636911928653717,-0.3925652801990509,-2.1151821613311768,-1.2124861478805542,-2.5723955631256104,0.9548728466033936,1.7250821590423584,-0.32854509353637695,1.486218810081482,1.5000838041305542,0.2135382443666458,1.8290942907333374,-0.7128830552101135,1.4743174314498901,-0.0077574108727276325,2.140444755554199,-0.9734758138656616,0.4780467748641968,1.047232985496521,-0.9654942154884338,-0.5451322793960571,1.5198307037353516,1.5490834712982178,-1.7548836469650269,1.8381704092025757,0.40804892778396606,-0.2782284915447235,3.0067570209503174,1.3385893106460571,0.04290491342544556,1.5621120929718018,1.5470161437988281,-1.461460828781128,-1.5983502864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diff --git a/src/constants/examples/kv/ex3.js b/src/constants/examples/kv/ex3.js
new file mode 100644
index 0000000..9d3b2b2
--- /dev/null
+++ b/src/constants/examples/kv/ex3.js
@@ -0,0 +1 @@
+export const kvEx3 = {"promptTokens":["On"," the"," deserted"," planet"," they"," discovered"," a"],"decodeSteps":[{"inputToken":" strange","inputTokenId":6283,"kvSnapshot":{"keys":[[[-1.1050492525100708,2.029740571975708,0.9042025804519653,-0.2304295003414154,0.5505644679069519,0.8528631925582886,0.1310260146856308,0.7505720853805542,-1.8175621032714844,0.143899068236351,0.1926005780696869,-0.652043879032135,0.6136986017227173,-0.20792093873023987,-0.7116473317146301,0.16473586857318878,0.4552529752254486,-0.21878336369991302,2.283104658126831,0.3611306846141815,-1.9167193174362183,0.35601651668548584,-0.5033861398696899,-1.0216662883758545,-0.062327511608600616,-0.5024545788764954,-0.48697105050086975,-0.5918087363243103,-0.011057578958570957,-0.4011770784854889,0.8747385144233704,-0.864720344543457,-0.7048558592796326,0.4516325891017914,-0.4865942597389221,0.2749515175819397,1.0590869188308716,0.3974701166152954,0.12999290227890015,0.4264041483402252,0.010657628066837788,0.2723386883735657,-0.6381274461746216,0.5010842084884644,-0.7430843710899353,-0.3572515845298767,0.5567625761032104,-0.0662224292755127,0.08850976824760437,0.5519891381263733,0.2165413498878479,-0.8581499457359314,1.2212527990341187,0.23587268590927124,-0.25743892788887024,1.0206935405731201,0.2594265341758728,-0.5473188161849976,0.08981715887784958,0.13813680410385132,-0.4844512641429901,-0.8781670928001404,-0.39898908138275146,1.4249356985092163],[-2.1015217304229736,2.69938588142395,1.720770239830017,0.06735403090715408,0.8563122153282166,0.507075309753418,0.5672464370727539,1.1351993083953857,-1.2756800651550293,1.0221080780029297,0.2478073239326477,0.9594515562057495,0.9112045764923096,0.0824609324336052,-1.3140476942062378,0.31746968626976013,-0.3076125383377075,-0.8064106702804565,2.382298469543457,0.6058070063591003,-2.9994657039642334,-0.8779362440109253,-0.6245948672294617,-1.232234001159668,-0.4650470018386841,0.3021223545074463,0.4573853313922882,0.08058059960603714,-0.26976853609085083,-0.3799256384372711,-1.6703431606292725,-0.7535884380340576,-1.5860121250152588,0.994138240814209,1.150132179260254,-0.12368791550397873,1.1407878398895264,1.1367337703704834,0.4640786051750183,0.11501576006412506,-0.5172367095947266,1.4128422737121582,-0.19445087015628815,1.1393758058547974,-0.910517156124115,-0.7142145037651062,0.7643955945968628,-0.3221496343612671,-1.6533739566802979,1.1148067712783813,0.7537150979042053,-1.1314157247543335,1.9118022918701172,0.7717965245246887,0.14899612963199615,2.5224146842956543,-0.013426600024104118,-0.21717041730880737,0.5551036596298218,1.8830153942108154,-1.555271863937378,-0.6648080945014954,-1.276104211807251,1.9811099767684937],[-1.1192528009414673,2.7518928050994873,0.45168522000312805,-1.6376782655715942,2.237165927886963,-0.6660266518592834,1.0613828897476196,-0.6451561450958252,-1.0356264114379883,0.4532129764556885,0.6259101033210754,-0.12367808073759079,0.8898878693580627,-0.9884915947914124,-0.3092809319496155,-0.9544172883033752,-0.17408154904842377,-0.8636876940727234,0.21581938862800598,-0.705682098865509,-0.5030336976051331,-0.7737992405891418,-0.5210972428321838,-1.065898060798645,-0.2815816104412079,1.0455188751220703,-0.7905868291854858,-0.5305277109146118,-0.31926628947257996,-1.2422455549240112,1.0452030897140503,-1.4241544008255005,-1.9244338274002075,1.7460078001022339,1.4547181129455566,0.9243418574333191,0.9644991159439087,1.8202420473098755,0.7438698410987854,-0.47462451457977295,-0.22504553198814392,0.41166242957115173,0.8763384222984314,1.003400206565857,-0.02198095992207527,0.3334241211414337,0.8109841346740723,-1.3874739408493042,-0.4488728642463684,1.534924864768982,-0.07265930622816086,-1.0798965692520142,1.1339833736419678,0.08368667960166931,-0.5484595894813538,1.2811479568481445,-0.3820825517177582,1.116855502128601,-0.017558570951223373,-1.174521803855896,-1.1754521131515503,-2.5377397537231445,-1.6084846258163452,1.7708523273468018],[-1.9810417890548706,3.466799259185791,0.8021884560585022,0.6396231651306152,0.614483118057251,0.6065323352813721,2.146284580230713,0.19703222811222076,-2.2406327724456787,0.6843730807304382,0.825978696346283,0.5936586856842041,0.5937108993530273,-0.7776598334312439,-1.4805448055267334,0.5468752980232239,2.192474603652954,-0.7705134153366089,0.5917728543281555,-2.1431772708892822,-1.4584715366363525,-2.4669301509857178,-1.0990965366363525,-1.1041781902313232,0.7125293612480164,0.2087523192167282,-0.4195097088813782,2.281562566757202,-1.404364824295044,-0.6573178768157959,-0.22810378670692444,-1.7966293096542358,-1.9843974113464355,0.8888174295425415,1.078465461730957,1.0579736232757568,1.9465382099151611,2.533804416656494,1.9893664121627808,-0.08958582580089569,-0.31155845522880554,2.9520206451416016,0.06608320027589798,2.35154390335083,-1.2360824346542358,-0.5984787940979004,1.2959010601043701,-0.908567488193512,-1.3712668418884277,0.775782585144043,2.189483880996704,-1.2816168069839478,0.7334055304527283,1.4579873085021973,-0.22378630936145782,1.9255948066711426,-0.5940923094749451,0.9099338054656982,1.0986762046813965,-0.07650993019342422,-0.17233291268348694,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diff --git a/src/constants/examples/kv/ex4.js b/src/constants/examples/kv/ex4.js
new file mode 100644
index 0000000..cf138b4
--- /dev/null
+++ b/src/constants/examples/kv/ex4.js
@@ -0,0 +1 @@
+export const kvEx4 = {"promptTokens":["I","EEE"," VIS"," conference"," highlights"," the"],"decodeSteps":[{"inputToken":" importance","inputTokenId":6817,"kvSnapshot":{"keys":[[[-1.5576591491699219,2.058478832244873,1.3060319423675537,0.2524546980857849,0.9934898018836975,0.3564787209033966,0.4260798394680023,0.7812840938568115,-2.273236036300659,0.2395511269569397,-0.1326839029788971,-0.05451151356101036,0.7474135756492615,-0.47063466906547546,-0.6061489582061768,0.021854471415281296,0.5444745421409607,-0.02226819470524788,2.760930061340332,-0.2801732122898102,-1.6989367008209229,0.28891825675964355,-0.2508653998374939,-1.3047235012054443,0.28415948152542114,-0.6497727632522583,-0.38214272260665894,0.02590346336364746,-0.6155605316162109,-0.7517723441123962,0.9011170268058777,-0.6145974397659302,-1.3105093240737915,0.1235223039984703,-0.44793805480003357,-0.37176209688186646,0.6886441707611084,0.13914698362350464,0.3355637490749359,0.5130960941314697,0.20180168747901917,0.2645183503627777,-0.2729761600494385,0.43337389826774597,-0.577684760093689,-0.4008170962333679,0.6545336246490479,-0.07693962007761002,-0.04108989238739014,0.16646192967891693,0.5629372596740723,-0.8928043246269226,0.9489826560020447,0.17634570598602295,0.6083218455314636,1.3647916316986084,-0.07527139782905579,-0.38080310821533203,0.17063561081886292,0.31056809425354004,-0.5342482924461365,-1.3824985027313232,-0.6333605051040649,1.2624069452285767],[-1.73524010181427,1.9578927755355835,1.9853399991989136,-0.12015821039676666,-1.1739479303359985,2.154581308364868,-0.7105542421340942,0.4799697697162628,0.7987873554229736,0.9885328412055969,1.3891102075576782,-0.4574945569038391,1.4641644954681396,-0.4664701223373413,-1.28872811794281,0.13778068125247955,-0.3799359202384949,0.6029072403907776,1.8246963024139404,0.05195623263716698,-2.274705648422241,1.144449234008789,-0.5031772255897522,-1.3462729454040527,0.7623036503791809,0.2409651279449463,-0.6774614453315735,-0.3263760209083557,1.2668845653533936,-0.7621572017669678,2.1608481407165527,-0.6022946834564209,-1.598789930343628,0.7841147184371948,0.10659129917621613,0.273212194442749,0.7987942695617676,1.2177609205245972,0.8445693850517273,0.31161120533943176,0.31080174446105957,1.117202877998352,-0.3464091122150421,0.9324164986610413,-0.8558388948440552,-1.4818384647369385,-1.4126232862472534,-0.9545815587043762,-0.1864931434392929,2.090402841567993,1.102231740951538,-1.4553834199905396,1.1122559309005737,-0.17125089466571808,0.40012529492378235,1.2590925693511963,0.9127323031425476,0.026110565289855003,-0.15170104801654816,2.004477024078369,-1.0078234672546387,-1.667026400566101,-0.8439847826957703,2.0566189289093018],[-2.3000876903533936,2.1209983825683594,0.42868703603744507,1.3006706237792969,0.7006363868713379,0.8841615319252014,-0.23507608473300934,1.6513261795043945,-2.196115732192993,0.3196524679660797,2.188753604888916,0.8261770009994507,1.0105171203613281,-1.3699970245361328,-1.0441933870315552,0.6244144439697266,-0.3268570601940155,-0.22889266908168793,1.1421620845794678,-0.46623268723487854,0.23669873178005219,0.11849205940961838,1.0128092765808105,-2.3786110877990723,-0.5207328200340271,-0.41784706711769104,0.1381780058145523,-0.1888325959444046,-0.9368128776550293,-1.4305357933044434,0.28219926357269287,-1.9158028364181519,-2.7503795623779297,0.5783637166023254,2.053698778152466,-0.6800717115402222,0.37765851616859436,0.3749504089355469,0.6837908625602722,0.5202951431274414,0.4475574195384979,1.3189736604690552,-0.10611756891012192,-0.8300746083259583,-1.6946170330047607,-0.7534488439559937,1.4285063743591309,-0.2691743075847626,0.5932228565216064,0.9155290722846985,0.7793372273445129,-1.3522142171859741,1.2399680614471436,-0.047847311943769455,-0.7046096324920654,1.6123427152633667,-0.36046648025512695,-2.710663318634033,-1.0989158153533936,1.4540780782699585,-0.48837751150131226,-1.0447266101837158,-1.071799635887146,1.839921236038208],[-3.106330156326294,1.9695698022842407,0.40801629424095154,1.1425851583480835,-0.026611166074872017,-0.054213959723711014,0.9097326397895813,0.4094056785106659,-0.782752275466919,0.8294837474822998,-0.5844053030014038,0.16000114381313324,-0.3007344901561737,-1.1459758281707764,-1.7010246515274048,-1.050544261932373,0.7832226157188416,-0.6322479844093323,2.3391008377075195,-0.418053537607193,-3.874323606491089,-0.1799314171075821,-0.6287530660629272,-1.3183561563491821,2.273509979248047,-0.02488795295357704,-0.1818852573633194,0.3863215148448944,-0.5936079621315002,-0.9964725375175476,-0.9310005903244019,-1.663125991821289,-2.8060271739959717,1.598570704460144,1.2143969535827637,-0.894165575504303,-0.36513301730155945,1.5045764446258545,0.20453235507011414,-0.13197582960128784,0.5050522685050964,1.667531132698059,0.061919260770082474,1.184562087059021,-0.9394956231117249,0.380497008562088,1.6666492223739624,0.08417461067438126,-1.9358190298080444,1.1490603685379028,1.683853030204773,0.4681017994880676,2.148205280303955,0.4411788582801819,-0.08792656660079956,1.886932373046875,0.43542930483818054,-0.479652464389801,0.12143810838460922,2.6838669776916504,-1.078577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diff --git a/src/constants/examples/kv/index.js b/src/constants/examples/kv/index.js
new file mode 100644
index 0000000..96c42dc
--- /dev/null
+++ b/src/constants/examples/kv/index.js
@@ -0,0 +1,7 @@
+import {kvEx0} from './ex0';
+import {kvEx1} from './ex1';
+import {kvEx2} from './ex2';
+import {kvEx3} from './ex3';
+import {kvEx4} from './ex4';
+
+export { kvEx0, kvEx1, kvEx2, kvEx3, kvEx4 };
diff --git a/src/routes/kv-cache/+page.svelte b/src/routes/kv-cache/+page.svelte
new file mode 100644
index 0000000..6aa20f9
--- /dev/null
+++ b/src/routes/kv-cache/+page.svelte
@@ -0,0 +1,780 @@
+<script lang="ts">
+	import {
+		tokens,
+		expandedBlock,
+		vectorHeight,
+		inputText,
+		rootRem,
+		sampling,
+		maxVectorHeight,
+		minVectorHeight,
+		maxVectorScale,
+		headContentHeight,
+		temperature,
+		modelData,
+		isFetchingModel,
+		selectedExampleIdx,
+		isMobile,
+		isOnBlockTransition,
+		blockIdx,
+		isModelRunning,
+		attentionHeadIdx,
+		predictedToken,
+		isTextbookOpen,
+		textbookCurrentPage
+	} from '~/store';
+	import { PreTrainedTokenizer } from '@xenova/transformers';
+	import Sankey from '~/components/Sankey.svelte';
+	import Attention from '~/components/Attention.svelte';
+	import SubsequentBlocks from '~/components/SubsequentBlocks.svelte';
+	import LinearSoftmax from '~/components/LinearSoftmax.svelte';
+	import Embedding from '~/components/Embedding.svelte';
+	import Mlp from '~/components/Mlp.svelte';
+
+	import { onMount } from 'svelte';
+	import classNames from 'classnames';
+	import { AutoTokenizer } from '@xenova/transformers';
+	import { ex0, ex1, ex2, ex3, ex4 } from '~/constants/examples';
+	import { kvEx0, kvEx1, kvEx2, kvEx3, kvEx4 } from '~/constants/examples/kv';
+	import BlockTransition from '~/components/BlockTransition.svelte';
+	import QKV from '~/components/QKV.svelte';
+	import WeightPopovers from '~/components/WeightPopovers.svelte';
+	import Textbook from '~/components/textbook/Textbook.svelte';
+
+	import { adjustTemperature, fakeRunWithCachedData, getProbabilities } from '~/utils/data';
+	import { textPages } from '~/utils/textbookPages';
+	import {
+		decodeStep,
+		kvCache,
+		isDecoding,
+		currentDecodeData,
+		promptTokenCount,
+		resetKVCache,
+		type KVCacheEntry,
+		type DecodeStepData
+	} from '~/store/kvcache';
+
+	let active = false;
+	let tokenizer: PreTrainedTokenizer | null = null;
+
+	// KV example data for each prompt
+	const cachedDataMap = [ex0, ex1, ex2, ex3, ex4];
+	const kvExamples = [kvEx0, kvEx1, kvEx2, kvEx3, kvEx4];
+
+	// Track which KV example to use after prefill animation finishes
+	let pendingKvExIdx = 0;
+	let kvReady = false; // true after prefill animation done
+	let prefillText = ''; // inputText captured at end of prefill
+	let ignoreInputTextChange = false; // guard against re-triggering prefill when we programmatically set inputText
+
+	// Set textbook to kv-cache pages immediately (before async tokenizer load)
+	const kvInferenceIdx = textPages.findIndex((p) => p.id === 'kv-inference');
+	if (kvInferenceIdx >= 0) {
+		textbookCurrentPage.set(kvInferenceIdx);
+	}
+
+	onMount(async () => {
+		const gpt2Tokenizer = await AutoTokenizer.from_pretrained('Xenova/gpt2');
+		tokenizer = gpt2Tokenizer;
+		active = true;
+
+		const unsubscribe = subscribeInputs(gpt2Tokenizer);
+		return unsubscribe;
+	});
+
+	// Watch for prefill animation completion
+	let prevModelRunning = false;
+	$: {
+		const running = $isModelRunning;
+		if (prevModelRunning && !running) {
+			// prefill animation just finished
+			kvReady = true;
+			prefillText = $inputText;
+			// Override sampled token with the greedy first decode token
+			const kvData = kvExamples[pendingKvExIdx];
+			const firstStep = kvData.decodeSteps[0];
+			if (firstStep) {
+				predictedToken.set({
+					rank: 0,
+					tokenId: firstStep.inputTokenId,
+					token: firstStep.inputToken,
+					logit: 0,
+					scaledLogit: 0,
+					expLogit: 1,
+					probability: 1
+				});
+			}
+		}
+		prevModelRunning = running;
+	}
+
+	// Subscribe inputs — always uses cached data (no live ONNX on this page)
+	const subscribeInputs = (tok: PreTrainedTokenizer) => {
+		const runPrefill = () => {
+			kvReady = false;
+			resetKVCache();
+			pendingKvExIdx = $selectedExampleIdx;
+
+			fakeRunWithCachedData({
+				cachedData: cachedDataMap[$selectedExampleIdx],
+				tokenizer: tok,
+				temperature: $temperature,
+				sampling: $sampling
+			});
+		};
+
+		const unsubscribeInputText = inputText.subscribe(() => {
+			if (ignoreInputTextChange) {
+				ignoreInputTextChange = false;
+				return;
+			}
+			runPrefill();
+		});
+
+		let initialTemperature = true;
+		const unsubscribeTemperature = temperature.subscribe((value) => {
+			if (initialTemperature) {
+				initialTemperature = false;
+				return;
+			}
+			if ($isDecoding) {
+				const step = $currentDecodeData;
+				const kvData = kvExamples[pendingKvExIdx];
+				const greedyNext = kvData.decodeSteps[$decodeStep];
+				if (step?.topLogits) {
+					updateDecodeStepProbabilities(tok, step, greedyNext);
+				}
+			} else if ($modelData?.logits) {
+				adjustTemperature({ tokenizer: tok, logits: $modelData.logits, temperature: value, sampling: $sampling });
+			}
+		});
+
+		let initialSampling = true;
+		const unsubscribeSampling = sampling.subscribe((value) => {
+			if (initialSampling) {
+				initialSampling = false;
+				return;
+			}
+			if ($isDecoding) {
+				const step = $currentDecodeData;
+				const kvData = kvExamples[pendingKvExIdx];
+				const greedyNext = kvData.decodeSteps[$decodeStep];
+				if (step?.topLogits) {
+					updateDecodeStepProbabilities(tok, step, greedyNext);
+				}
+			} else if ($modelData?.logits) {
+				adjustTemperature({ tokenizer: tok, logits: $modelData.logits, temperature: $temperature, sampling: value });
+			}
+		});
+
+		return () => {
+			unsubscribeInputText();
+			unsubscribeTemperature();
+			unsubscribeSampling();
+		};
+	};
+
+	// Reconstruct a full-length sparse logit array from top-N pairs
+	function reconstructLogits(topLogits: [number, number][], vocabSize = 50257): number[] {
+		const logits = new Array(vocabSize).fill(-Infinity);
+		for (const [id, logit] of topLogits) {
+			logits[id] = logit;
+		}
+		return logits;
+	}
+
+	// Update modelData probabilities for a decode step using its topLogits
+	function updateDecodeStepProbabilities(
+		tok: PreTrainedTokenizer,
+		stepData: DecodeStepData,
+		greedyNextToken: { inputTokenId: number; inputToken: string } | undefined
+	) {
+		if (!stepData.topLogits || !tok) return;
+		const logits = reconstructLogits(stepData.topLogits);
+		const { probabilities } = getProbabilities({
+			tokenizer: tok,
+			logits,
+			temperature: $temperature,
+			sampling: $sampling
+		});
+		// Find (or fake) the greedy next token entry to use as "sampled"
+		const greedyProb = greedyNextToken
+			? probabilities.find((p) => p.tokenId === greedyNextToken.inputTokenId) ?? {
+					rank: 0,
+					tokenId: greedyNextToken.inputTokenId,
+					token: greedyNextToken.inputToken,
+					logit: logits[greedyNextToken.inputTokenId] ?? 0,
+					scaledLogit: (logits[greedyNextToken.inputTokenId] ?? 0) / $temperature,
+					expLogit: 1,
+					probability: 1
+				}
+			: probabilities[0];
+
+		modelData.update((d) => ({ ...d, logits, probabilities, sampled: greedyProb }));
+		predictedToken.set(greedyProb);
+	}
+
+	// Build kvCache entries for a given decode step (0-indexed)
+	function buildKVCacheEntries(kvData: typeof kvEx0, stepIdx: number): KVCacheEntry[] {
+		const stepData = kvData.decodeSteps[stepIdx];
+		const seqLen = stepData.kvSnapshot.keys[0].length;
+		const promptTokens = kvData.promptTokens;
+
+		return Array.from({ length: seqLen }, (_, i) => {
+			const tokenStr =
+				i < promptTokens.length
+					? promptTokens[i]
+					: kvData.decodeSteps[i - promptTokens.length].inputToken;
+			return {
+				token: tokenStr,
+				// keys[headIdx][tokenIdx] → per-token, all-heads K vectors
+				keys: stepData.kvSnapshot.keys.map((headKeys: number[][]) => headKeys[i]),
+				values: stepData.kvSnapshot.values.map((headVals: number[][]) => headVals[i])
+			};
+		});
+	}
+
+	// Show the predicted next token in the LinearSoftmax panel
+	function setPredictedNextToken(kvData: typeof kvEx0, afterStepIdx: number) {
+		// afterStepIdx: 0-indexed step just processed; next predicted = decodeSteps[afterStepIdx+1].inputToken
+		const next = kvData.decodeSteps[afterStepIdx + 1];
+		if (next) {
+				predictedToken.set({
+				rank: 0,
+				tokenId: next.inputTokenId,
+				token: next.inputToken,
+				logit: 0,
+				scaledLogit: 0,
+				expLogit: 1,
+				probability: 1
+			});
+		}
+	}
+
+	// Advance to next decode step
+	function nextStep() {
+		if (!kvReady) return;
+		const kvData = kvExamples[pendingKvExIdx];
+		const nextIdx = $decodeStep; // 0-indexed into decodeSteps
+		if (nextIdx >= kvData.decodeSteps.length) return;
+
+		const stepData = kvData.decodeSteps[nextIdx];
+		const entries = buildKVCacheEntries(kvData, nextIdx);
+
+		promptTokenCount.set(kvData.promptTokens.length);
+		kvCache.set(entries);
+		currentDecodeData.set(stepData as DecodeStepData);
+
+		// Show only the current decode token in QKV/MLP/Embedding columns
+		tokens.set([stepData.inputToken]);
+
+		// Accumulate decoded tokens in the text box without re-triggering prefill
+		const decodedSoFar = kvData.decodeSteps
+			.slice(0, nextIdx + 1)
+			.map((s) => s.inputToken)
+			.join('');
+		ignoreInputTextChange = true;
+		inputText.set(prefillText + decodedSoFar);
+
+		// Update probabilities panel with this step's distribution + highlight greedy next token
+		const greedyNext = kvData.decodeSteps[nextIdx + 1];
+		if (tokenizer && stepData.topLogits) {
+			updateDecodeStepProbabilities(tokenizer, stepData as DecodeStepData, greedyNext);
+		} else {
+			setPredictedNextToken(kvData, nextIdx);
+		}
+
+		decodeStep.set(nextIdx + 1);
+	}
+
+	// Go back to previous decode step (or back to prefill view)
+	function prevStep() {
+		const cur = $decodeStep;
+		if (cur <= 0) return;
+
+		const newStep = cur - 1;
+		decodeStep.set(newStep);
+
+		if (newStep === 0) {
+			// Back to prefill: restore all prompt tokens and prefill predictions
+			const prefillData = cachedDataMap[pendingKvExIdx];
+			tokens.set(prefillData.tokens);
+			kvCache.set([]);
+			currentDecodeData.set(null);
+			ignoreInputTextChange = true;
+			inputText.set(prefillText);
+			if (tokenizer && $modelData?.logits) {
+				adjustTemperature({
+					tokenizer,
+					logits: $modelData.logits,
+					temperature: $temperature,
+					sampling: $sampling
+				});
+			}
+			return;
+		}
+
+		// Go back one step: rebuild kvCache from step newStep - 1 (0-indexed)
+		const kvData = kvExamples[pendingKvExIdx];
+		const prevIdx = newStep - 1;
+		const stepData = kvData.decodeSteps[prevIdx];
+		const entries = buildKVCacheEntries(kvData, prevIdx);
+
+		promptTokenCount.set(kvData.promptTokens.length);
+		kvCache.set(entries);
+		currentDecodeData.set(stepData as DecodeStepData);
+		tokens.set([stepData.inputToken]);
+
+		// Restore accumulated text to match this step
+		const decodedSoFar = kvData.decodeSteps
+			.slice(0, prevIdx + 1)
+			.map((s: { inputToken: string }) => s.inputToken)
+			.join('');
+		ignoreInputTextChange = true;
+		inputText.set(prefillText + decodedSoFar);
+
+		const greedyNext = kvData.decodeSteps[prevIdx + 1];
+		if (tokenizer && stepData.topLogits) {
+			updateDecodeStepProbabilities(tokenizer, stepData as DecodeStepData, greedyNext);
+		} else {
+			setPredictedNextToken(kvData, prevIdx);
+		}
+	}
+
+	// Visual elements
+	let vizHeight = 0;
+	let titleHeight = rootRem * 5;
+
+	const calculateVectorHeight = () => {
+		const gaps = rootRem * 0.5 * ($tokens.length - 1);
+		const vectorHeightVal = Math.min(
+			Math.max((vizHeight - titleHeight - gaps) / $tokens.length / maxVectorScale, minVectorHeight),
+			maxVectorHeight
+		);
+		vectorHeight.set(vectorHeightVal);
+		headContentHeight.set(Math.max($tokens.length * vectorHeightVal * 3 + gaps, rootRem * 20));
+	};
+
+	$: if (vizHeight || $tokens.length) {
+		calculateVectorHeight();
+	}
+
+	$: maxDecodeStep = kvExamples[pendingKvExIdx]?.decodeSteps?.length ?? 0;
+</script>
+
+<div
+	class:active
+	class:decode-mode={$isDecoding}
+	class="main-section h-full w-full"
+	style={`--vector-height: ${$vectorHeight}px;--title-height: ${titleHeight}px;--content-height:${vizHeight - titleHeight}px;`}
+>
+	{#if kvReady && !$isModelRunning}
+		<div class="decode-controls">
+			<button
+				class="step-btn"
+				on:click={prevStep}
+				disabled={$decodeStep <= 0}
+			>
+				← Prev
+			</button>
+			<span class="step-label">
+				{#if $decodeStep === 0}
+					Prefill complete — click Next → to decode
+				{:else}
+					Decode step {$decodeStep} / {maxDecodeStep}
+				{/if}
+			</span>
+			<button
+				class="step-btn"
+				on:click={nextStep}
+				disabled={$decodeStep >= maxDecodeStep}
+			>
+				Next →
+			</button>
+		</div>
+	{/if}
+
+	{#if !!$expandedBlock.id}
+		<div
+			class={classNames('dim', `${$expandedBlock.id || ''}`)}
+		></div>
+		<div
+			class={classNames('dim-partial left', `${$expandedBlock.id || ''}`)}
+		></div>
+		<div
+			class={classNames('dim-partial right', `${$expandedBlock.id || ''}`)}
+		></div>
+	{/if}
+	<div class="sankey opacity-1" class:attention={$expandedBlock.id === 'attention'}>
+		<Sankey />
+	</div>
+	<div class="nodes resize-watch">
+		<div class="steps" class:expanded={!!$expandedBlock.id} bind:offsetHeight={vizHeight}>
+			<Embedding className="step" />
+			<div class="blocks relative">
+				<div class="block-steps main" class:initial={$blockIdx === 0}>
+					<QKV className="step" />
+					<Attention className="step" />
+					<Mlp className="step" />
+				</div>
+				<div
+					class="block-steps next"
+					class:hide={!$isOnBlockTransition}
+					class:initial={$blockIdx === 0}
+				>
+					<QKV className="step" />
+					<Attention className="step" />
+					<Mlp className="step" />
+				</div>
+				<div class="transition-watch" class:hide={!$isOnBlockTransition}></div>
+			</div>
+			<SubsequentBlocks className="step" />
+			<LinearSoftmax className="step" />
+		</div>
+		<WeightPopovers />
+		<BlockTransition />
+	</div>
+</div>
+
+{#if !$isMobile}
+	<Textbook showTextCard={$isTextbookOpen} />
+{/if}
+
+<style lang="scss">
+	.main-section {
+		opacity: 0;
+		&.active {
+			opacity: 1;
+		}
+	}
+
+	.decode-controls {
+		position: fixed;
+		bottom: 1.5rem;
+		left: 50%;
+		transform: translateX(-50%);
+		display: flex;
+		align-items: center;
+		gap: 1rem;
+		background: white;
+		border: 1px solid theme('colors.gray.200');
+		border-radius: 2rem;
+		padding: 0.5rem 1.25rem;
+		z-index: 9000;
+		box-shadow: 0 2px 12px rgba(0, 0, 0, 0.08);
+		font-size: 0.85rem;
+
+		.step-btn {
+			color: theme('colors.gray.600');
+			cursor: pointer;
+			padding: 0.25rem 0.5rem;
+			border-radius: 0.25rem;
+			transition: background-color 0.15s;
+
+			&:hover:not(:disabled) {
+				background-color: theme('colors.gray.100');
+				color: theme('colors.gray.800');
+			}
+
+			&:disabled {
+				opacity: 0.35;
+				cursor: not-allowed;
+			}
+		}
+
+		.step-label {
+			color: theme('colors.gray.500');
+			white-space: nowrap;
+			min-width: 14rem;
+			text-align: center;
+		}
+	}
+
+	.nodes {
+		height: 100%;
+		width: 100%;
+		padding: 1rem 0 3rem 0;
+		position: relative;
+	}
+	.steps {
+		position: relative;
+		width: 100%;
+		height: 100%;
+		position: relative;
+		display: grid;
+		grid-template-columns: auto 3.5fr 0.5fr 0.5fr;
+
+		&.expanded {
+			:global(.step > .title) {
+				padding-bottom: 3rem;
+			}
+		}
+
+		.blocks {
+			position: relative;
+			width: 100%;
+			height: 100%;
+
+			.block-steps {
+				height: 100%;
+				width: 100%;
+				position: absolute;
+				display: grid;
+				grid-template-columns: 0.5fr 2fr 1fr;
+			}
+			.block-steps.main {
+				transform-origin: 3rem center;
+				top: 0;
+				left: 0;
+			}
+			.block-steps.next {
+				transform-origin: right center;
+				justify-content: end;
+				top: 0;
+				right: 0;
+				pointer-events: none;
+			}
+
+			.transition-watch {
+				position: absolute;
+				top: 0;
+				left: 0;
+				height: 100%;
+				width: 100%;
+				pointer-events: none;
+			}
+
+			.hide {
+				display: none;
+			}
+		}
+	}
+
+	.dim {
+		position: absolute;
+		top: 0;
+		left: 0;
+		width: 100%;
+		height: 100%;
+		z-index: $DIM_INDEX;
+		background-color: white;
+		opacity: 0.7;
+		user-select: none;
+
+		&.attention {
+			z-index: 0;
+		}
+	}
+	.dim-partial {
+		user-select: none;
+		z-index: $PARTIAL_DIM_INDEX;
+		position: absolute;
+		top: 0;
+		height: 100%;
+
+		&.right {
+			right: 0;
+			background: linear-gradient(90deg, rgba(255, 255, 255, 0) 0%, rgba(255, 255, 255, 1) 80%);
+		}
+		&.left {
+			left: 0;
+			background: linear-gradient(-90deg, rgba(255, 255, 255, 0) 0%, rgba(255, 255, 255, 1) 80%);
+		}
+
+		&.attention {
+			&.left {
+				width: 20%;
+			}
+			&.right {
+				width: 20%;
+			}
+		}
+	}
+	.sankey {
+		position: absolute;
+		left: 0;
+		top: 0;
+		width: 100%;
+		height: 100%;
+
+		&.attention {
+			:global(.sankey-top) {
+				z-index: $EXPANDED_ATTENTION_INDEX !important;
+				pointer-events: none;
+			}
+		}
+	}
+
+	:global(.step) {
+		height: 100%;
+		display: grid;
+		grid-template-rows: var(--title-height) 1fr;
+	}
+
+	:global(.step > .title) {
+		z-index: $COLUMN_TITLE_INDEX;
+		display: flex;
+		flex-direction: column;
+		justify-content: end;
+		grid-row: 1;
+		color: theme('colors.gray.400');
+		white-space: nowrap;
+		padding-bottom: 2rem;
+		overflow: visible;
+		min-width: 0;
+		transition: all 0.5s;
+		cursor: default;
+
+		&:hover {
+			color: theme('colors.gray.600');
+		}
+	}
+
+	:global(.step > .title.expandable) {
+		cursor: pointer;
+	}
+
+	:global(.step .content) {
+		grid-row: 2;
+		height: fit-content;
+	}
+
+	:global(.column) {
+		display: flex;
+		flex-direction: column;
+		gap: 0.5rem;
+		position: relative;
+
+		:global(.cell) {
+			height: var(--vector-height);
+			display: flex;
+			gap: 1rem;
+			align-items: center;
+			position: relative;
+		}
+
+		:global(.subtitle) {
+			position: absolute;
+			top: 0;
+			transform: translateY(calc(-100% - 1rem));
+			text-align: center;
+			font-size: 0.8rem;
+			color: theme('colors.gray.400');
+			width: 100%;
+			z-index: $COLUMN_TITLE_INDEX;
+		}
+	}
+
+	:global(.vector),
+	:global(.sub-vector) {
+		position: relative;
+		z-index: $VECTOR_INDEX;
+		width: 12px;
+		height: var(--vector-height);
+		flex-shrink: 0;
+		justify-content: start;
+	}
+	:global(.cell.x1-12),
+	:global(.vector.x1-12),
+	:global(.sub-vector.x1-12) {
+		height: calc(var(--vector-height) / 12);
+	}
+
+	:global(.cell.x3),
+	:global(.vector.x3),
+	:global(.sub-vector.x3) {
+		height: calc(var(--vector-height) * 3);
+	}
+	:global(.cell.x4),
+	:global(.vector.x4),
+	:global(.sub-vector.x4) {
+		height: calc(var(--vector-height) * 3.1);
+	}
+
+	:global(.vector.vocab),
+	:global(.sub-vector.vocab) {
+		height: 100%;
+		width: 0;
+	}
+
+	:global(.sub-vector.head-rest) {
+		flex: 1 0 0;
+	}
+
+	:global(.label) {
+		font-size: 0.9rem;
+		color: theme('colors.gray.700');
+		z-index: $VECTOR_INDEX;
+		display: inline;
+		max-width: 7rem;
+		overflow: hidden;
+		text-overflow: ellipsis;
+		text-align: right;
+		line-height: var(--vector-height);
+		height: var(--vector-height);
+		flex-shrink: 0;
+	}
+	:global(.label.float) {
+		position: absolute;
+		left: -0.8rem;
+		transform: translateX(-100%);
+	}
+
+	:global(.decode-mode .mlp .label) {
+		display: none;
+	}
+	:global(.label.float-right) {
+		position: absolute;
+		left: -0.8rem;
+	}
+
+	:global(.ellipsis) {
+		white-space: nowrap;
+		overflow: hidden;
+		text-overflow: ellipsis;
+	}
+
+	:global(.bounding) {
+		position: absolute;
+		box-sizing: content-box;
+		top: -0.5rem;
+		padding: 0.5rem 0;
+		left: 0;
+		height: 100%;
+		border: 2px dashed theme('colors.gray.300');
+		border-radius: 0.5rem;
+		transition: opacity 0.5s;
+		opacity: 0;
+		pointer-events: none;
+	}
+	:global(.bounding.active) {
+		opacity: 0.8;
+	}
+
+	:global(.popover) {
+		z-index: $POPOVER_INDEX;
+		width: max-content;
+	}
+
+	:global(.tooltip) {
+		z-index: $TOOLTIP_INDEX;
+		background-color: white !important;
+		color: theme('colors.gray.600') !important;
+		border: 1px solid theme('colors.gray.200') !important;
+		padding: 0.2rem 0.5rem !important;
+		font-size: 0.8rem !important;
+		white-space: nowrap;
+		font-weight: 300 !important;
+		border-color: theme('colors.gray.200') !important;
+	}
+
+	:global(svg g.path-group) {
+		transition: opacity 0.5s;
+	}
+	:global(div.step > div) {
+		transition: opacity 0.5s;
+	}
+	:global(div.step .column) {
+		transition: opacity 0.5s;
+	}
+</style>
diff --git a/src/routes/kv-cache/+page.ts b/src/routes/kv-cache/+page.ts
new file mode 100644
index 0000000..189f71e
--- /dev/null
+++ b/src/routes/kv-cache/+page.ts
@@ -0,0 +1 @@
+export const prerender = true;
diff --git a/src/store/kvcache.ts b/src/store/kvcache.ts
new file mode 100644
index 0000000..7645587
--- /dev/null
+++ b/src/store/kvcache.ts
@@ -0,0 +1,38 @@
+import { writable, derived } from 'svelte/store';
+
+export const decodeStep = writable<number>(0);
+// 0 = prefill complete, 1+ = decode steps
+
+export type KVCacheEntry = {
+	token: string;
+	keys: number[][];   // [12 heads, 64] — all heads for this token
+	values: number[][];  // [12 heads, 64]
+};
+
+export const kvCache = writable<KVCacheEntry[]>([]);
+// Grows by one row per step advance
+
+export const isDecoding = derived(decodeStep, ($s) => $s > 0);
+
+export type DecodeStepData = {
+	inputToken: string;
+	inputTokenId: number;
+	kvSnapshot: {
+		keys: number[][][];   // [12 heads, seq_len, 64]
+		values: number[][][]; // [12 heads, seq_len, 64]
+	};
+	attentionOutputs: Record<string, { data: number[][]; dims: number[]; size: number }>;
+	topLogits?: [number, number][];  // [[tokenId, logit], ...] top-50 by raw logit
+	logits?: number[];
+};
+
+export const currentDecodeData = writable<DecodeStepData | null>(null);
+
+export const promptTokenCount = writable<number>(0);
+
+export function resetKVCache() {
+	decodeStep.set(0);
+	kvCache.set([]);
+	currentDecodeData.set(null);
+	promptTokenCount.set(0);
+}
diff --git a/src/utils/textbookPages.ts b/src/utils/textbookPages.ts
index bc95163..7f1482b 100644
--- a/src/utils/textbookPages.ts
+++ b/src/utils/textbookPages.ts
@@ -561,12 +561,103 @@ export const textPages: TextbookPage[] = [
 		out: () => {
 			removeHighlightFromElements(['.operation-col.dropout']);
 		}
+	},
+	// ── KV Cache Explainer pages ──────────────────────────────────────────
+	{
+		id: 'kv-inference',
+		title: 'What is Inference?',
+		content: `<p>After training, the model's weights are fixed. <strong>Inference</strong> is using those weights to generate text — one token at a time, each pass predicting the next most probable word.</p>
+<figure class="tb-figure">
+  <img src="https://miro.medium.com/0*sexO6adGhaKr7aH0.gif" alt="GPT-2 generating tokens autoregressively" class="tb-img" loading="lazy" />
+  <figcaption>GPT-2 generating tokens one-by-one autoregressively.</figcaption>
+</figure>
+<p>KV caching makes this ~<strong>5× faster</strong> — benchmarks on a T4 GPU show 12s vs 61s for 1,000 tokens.</p>
+<p class="tb-citation">João Lages, <a href="https://medium.com/@joaolages/kv-caching-explained-276520203249" target="_blank" rel="noopener" class="tb-cite-link">"KV Caching Explained"</a>, <em>Medium</em>, Oct 2023.</p>`,
+		on: () => {
+			highlightElements(['.input-form']);
+		},
+		out: () => {
+			removeHighlightFromElements(['.input-form']);
+		}
+	},
+	{
+		id: 'kv-prefill',
+		title: 'Prefill Phase',
+		content: `<p>When you submit a prompt, all tokens flow through every block in a single pass — the <strong>prefill</strong> phase. Each token's <span class="red">Key</span> and <span class="green">Value</span> are computed and saved.</p>
+<figure class="tb-figure">
+  <img src="https://developer-blogs.nvidia.com/wp-content/uploads/2023/11/key-value-caching_.png" alt="KV caching: prefill and decode phases" class="tb-img" loading="lazy" />
+  <figcaption>Prefill processes all prompt tokens at once; decode reuses the stored K/V.</figcaption>
+</figure>
+<p class="tb-citation">S. Verma &amp; N. Vaidya, <a href="https://developer.nvidia.com/blog/mastering-llm-techniques-inference-optimization/" target="_blank" rel="noopener" class="tb-cite-link">"Mastering LLM Techniques: Inference Optimization"</a>, <em>NVIDIA</em>, Nov 2023.</p>`,
+		on: () => {
+			highlightElements(['.step.embedding', '.step.attention']);
+		},
+		out: () => {
+			removeHighlightFromElements(['.step.embedding', '.step.attention']);
+		}
+	},
+	{
+		id: 'kv-cache-intro',
+		title: 'The KV Cache',
+		content: `<p>The <strong>KV cache</strong> stores <span class="red">Key</span> and <span class="green">Value</span> vectors for every token × head × layer. GPT-2: 12 layers × 12 heads × 64 dims = 9,216 stored values per token, reused on every decode step.</p>
+<figure class="tb-figure">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/6527e89a8808d80ccff88b7a/DbL2RbXFRoMWA5CrOaGB8.png" alt="K/V pairs accumulating in the cache" class="tb-img" loading="lazy" />
+  <figcaption>Each new token appends its K/V pair to the growing cache.</figcaption>
+</figure>
+<p class="tb-citation">Not Lain, <a href="https://huggingface.co/blog/not-lain/kv-caching" target="_blank" rel="noopener" class="tb-cite-link">"KV Caching"</a>, <em>Hugging Face Blog</em>, Jan 2025.</p>`,
+		on: () => {
+			highlightElements(['.step.attention .decode-attention']);
+		},
+		out: () => {
+			removeHighlightFromElements(['.step.attention .decode-attention']);
+		}
+	},
+	{
+		id: 'kv-decode',
+		title: 'Decode Phase',
+		content: `<p>In the <strong>decode</strong> phase only the new token passes through the network. Its K and V are appended to the cache; all prior pairs are reused — no recomputation. Click <strong>Next →</strong> to step through it.</p>
+<figure class="tb-figure">
+  <img src="https://miro.medium.com/1*uyuyOW1VBqmF5Gtv225XHQ.gif" alt="Comparison: with and without KV caching" class="tb-img" loading="lazy" />
+  <figcaption>Without caching every token is recomputed from scratch (top); with caching only the new token is processed (bottom).</figcaption>
+</figure>
+<p class="tb-citation">João Lages, <a href="https://medium.com/@joaolages/kv-caching-explained-276520203249" target="_blank" rel="noopener" class="tb-cite-link">"KV Caching Explained"</a>, <em>Medium</em>, Oct 2023.</p>`,
+		on: () => {
+			highlightElements(['.decode-controls']);
+		},
+		out: () => {
+			removeHighlightFromElements(['.decode-controls']);
+		}
+	},
+	{
+		id: 'kv-attention-decode',
+		title: 'Attention During Decode',
+		content: `<p>During decode, attention has one <span class="blue">Query</span> but N cached <span class="red">Keys</span> and <span class="green">Values</span>. The single Q dot-products with all cached K → 1×N weights → weighted sum of V → output.</p>
+<figure class="tb-figure">
+  <img src="https://miro.medium.com/1*8xqD4AYTwn6mQXNw0uhDCg.gif" alt="Attention computation step-by-step during decode" class="tb-img" loading="lazy" />
+  <figcaption>The new token's Query attends to all cached Keys; no causal mask needed.</figcaption>
+</figure>
+<p class="tb-citation">João Lages, <a href="https://medium.com/@joaolages/kv-caching-explained-276520203249" target="_blank" rel="noopener" class="tb-cite-link">"KV Caching Explained"</a>, <em>Medium</em>, Oct 2023.</p>`,
+		on: () => {
+			highlightElements(['.step.attention .decode-attention']);
+		},
+		out: () => {
+			removeHighlightFromElements(['.step.attention .decode-attention']);
+		}
+	},
+	{
+		id: 'kv-autoregressive',
+		title: 'Autoregressive Loop',
+		content: `<p>Each decoded token feeds back as the next input — the <strong>autoregressive loop</strong>. The cache grows one column per step. Memory per token: <code>2 × layers × (heads × dim) × bytes</code>.</p>
+<figure class="tb-figure">
+  <img src="https://developer-blogs.nvidia.com/wp-content/uploads/2023/11/comparison-attention-mechanisms.png" alt="MHA, GQA, and MQA attention variants" class="tb-img" loading="lazy" />
+  <figcaption>At scale, MQA and GQA share K/V across heads to reduce cache size without sacrificing quality.</figcaption>
+</figure>
+<p class="tb-citation">S. Verma &amp; N. Vaidya, <a href="https://developer.nvidia.com/blog/mastering-llm-techniques-inference-optimization/" target="_blank" rel="noopener" class="tb-cite-link">"Mastering LLM Techniques: Inference Optimization"</a>, <em>NVIDIA</em>, Nov 2023.</p>`,
+		on: () => {
+			highlightElements(['.decode-controls', '.step.softmax']);
+		},
+		out: () => {
+			removeHighlightFromElements(['.decode-controls', '.step.softmax']);
+		}
 	}
-	// {
-	// 	id: 'final',
-	// 	title: `Let's explore!`,
-	// 	content: '',
-	// 	on: () => {},
-	// 	out: () => {}
-	// }
 ];
diff --git a/svelte.config.js b/svelte.config.js
index 5dd4952..ff7f35a 100644
--- a/svelte.config.js
+++ b/svelte.config.js
@@ -21,7 +21,7 @@ const config = {
 		}),
 		prerender: {
 			// List the specific routes to prerender
-			entries: ['/' /* other routes if needed */]
+			entries: ['/', '/kv-cache']
 		},
 		alias: {
 			'~': './src'
diff --git a/vite.config.ts b/vite.config.ts
index 9455ad0..0515d98 100644
--- a/vite.config.ts
+++ b/vite.config.ts
@@ -1,12 +1,13 @@
 import { sveltekit } from '@sveltejs/kit/vite';
 import { defineConfig } from 'vite';
+import { resolve } from 'path';
 
 export default defineConfig({
 	plugins: [sveltekit()],
 	css: {
 		preprocessorOptions: {
 			scss: {
-				additionalData: `@import 'src/styles/variables.scss';`
+				additionalData: `@import '${resolve('src/styles/variables.scss').replace(/\\/g, '/')}';`
 			}
 		}
 	},