diff --git a/docs/bug_reports/PR_BODY_encoder_divergence.md b/docs/bug_reports/PR_BODY_encoder_divergence.md
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+## Title
+Bug: deterministic non-incremental vs incremental divergence at token 50 (encoder path mismatch)
+
+## What this PR adds
+- Adds a focused bug dossier with reproducible commands and artifacts:
+  - `docs/bug_reports/encoder_divergence_nonincremental_vs_incremental.md`
+- Adds original-author-commit reproduction artifacts proving issue predates local changes:
+  - `perf/audio_runs/commit-compare-e6d193e-20260209T000000Z/comparison.json`
+  - `perf/audio_runs/commit-compare-e6d193e-20s-20260209T000000Z/comparison.json`
+- Adds a committed 20s fixture used by the report's token-50 claim:
+  - `perf/reference_audio/Paul_Solt_Ideating-and-developing-with-ChatGPT-Pro_mono_16k_20s.wav`
+
+## Problem statement
+On the same model/audio/settings, non-incremental file decode (`generate.py` with `model.encode`) diverges from incremental decode (`encode_step`) at output token index 50.
+This index is documented against the included 20s fixture (and may differ for different audio).
+
+## Repro
+See:
+- `docs/bug_reports/encoder_divergence_nonincremental_vs_incremental.md`
+
+## Key evidence
+- First divergence index pinned at 50 across decoder `sliding_window` sweep (128..16384).
+- Mel parity and conv parity hold through early region; first conv mismatch occurs later (pos 134).
+- Divergence localizes to encoder transformer full-vs-cached history path (layer 0 with history present).
+- Same signature reproduced at original-author commit `e6d193e85e84e30f26e370c66973ce287b8a9d57`.
+
+## Why this matters
+This causes non-incremental transcription quality collapse to PAD-heavy/special-token-heavy output relative to incremental path, limiting usable clip length for file transcription.
+
+## Proposed next step for maintainers
+Treat incremental encoder path as correctness baseline and enforce full-vs-incremental equivalence checks while investigating encoder full-sequence vs cached-history attention semantics.
diff --git a/docs/bug_reports/encoder_divergence_nonincremental_vs_incremental.md b/docs/bug_reports/encoder_divergence_nonincremental_vs_incremental.md
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+# Bug Report: Non-incremental vs Incremental Encoder Divergence (first token mismatch at index 50)
+
+## Summary
+On Voxtral realtime MLX inference, non-incremental file decoding (`generate.py` path using `model.encode`) and incremental decoding (`encode_step` path) diverge deterministically at output token index **50** on the same audio/model/settings.
+
+Important: the `50` index is tied to the included 20s fixture below and may differ for other audio.
+
+This appears to be an **encoder transformer full-sequence vs cached-history semantic mismatch**, not a decoder sliding-window issue.
+
+## Scope
+- Model: `mlx-community/Voxtral-Mini-4B-Realtime-6bit`
+- Audio fixture (included in this PR): `perf/reference_audio/Paul_Solt_Ideating-and-developing-with-ChatGPT-Pro_mono_16k_20s.wav`
+- Temperature: `0.0` (greedy)
+- STFT backend: `dft` (for parity runs)
+
+## Why this report is high confidence
+The divergence was reproduced on both:
+- current branch state (instrumented runs), and
+- original-author commit `e6d193e85e84e30f26e370c66973ce287b8a9d57`.
+
+So this is not introduced by recent local changes.
+
+## Minimal Repro (self-contained, 20s fixture)
+```bash
+PYTHONPATH=. .venv313/bin/python - <<'PY'
+from pathlib import Path
+import mlx.core as mx
+from voxmlx import load_model, _build_prompt_tokens
+from voxmlx.audio import load_audio, pad_audio, log_mel_spectrogram, log_mel_spectrogram_step, SAMPLES_PER_TOKEN
+from voxmlx.cache import RotatingKVCache
+
+def first_diff(a,b):
+    for i,(x,y) in enumerate(zip(a,b)):
+        if x!=y: return i
+    return None if len(a)==len(b) else min(len(a),len(b))
+
+def inc_embeds(model, audio_padded):
+    at=ct1=ct2=ec=ds=None
+    parts=[]
+    for i in range(0,len(audio_padded),SAMPLES_PER_TOKEN):
+        mel,at=log_mel_spectrogram_step(audio_padded[i:i+SAMPLES_PER_TOKEN],at)
+        out,ct1,ct2,ec,ds=model.encode_step(mel,ct1,ct2,ec,ds)
+        if out is not None and out.shape[0]>0: parts.append(out)
+    return mx.concatenate(parts,axis=0)
+
+def decode(model, embeds, prompt_tokens, n_delay, eos, sw=8192):
+    t=model.time_embedding(mx.array([n_delay],dtype=mx.float32))
+    pre=len(prompt_tokens)
+    text=model.language_model.embed(mx.array([prompt_tokens]))[0]
+    cache=[RotatingKVCache(sw) for _ in range(len(model.language_model.layers))]
+    logits=model.decode((text+embeds[:pre])[None,:,:],t,"causal",cache)
+    mx.eval(logits,*[x for c in cache for x in (c.keys,c.values)])
+    y=mx.argmax(logits[0,-1:],axis=-1).squeeze()
+    out=[]
+    for pos in range(pre, embeds.shape[0]):
+        tok=model.language_model.embed(y.reshape(1,1))[0,0]
+        nlogits=model.decode((embeds[pos]+tok)[None,None,:],t,mask=None,cache=cache)
+        y_next=mx.argmax(nlogits[0,-1:],axis=-1).squeeze()
+        tid=int(y.item()); out.append(tid); y=y_next
+    return out
+
+model,sp,_=load_model("mlx-community/Voxtral-Mini-4B-Realtime-6bit")
+audio=load_audio("perf/reference_audio/Paul_Solt_Ideating-and-developing-with-ChatGPT-Pro_mono_16k_20s.wav")
+audio=pad_audio(audio)
+prompt,n_delay=_build_prompt_tokens(sp)
+emb_non=model.encode(log_mel_spectrogram(audio))
+emb_inc=inc_embeds(model,audio)
+t_non=decode(model,emb_non,prompt,n_delay,sp.eos_id)
+t_inc=decode(model,emb_inc,prompt,n_delay,sp.eos_id)
+print("first_divergence", first_diff(t_non,t_inc))
+PY
+```
+
+## Key Observations
+
+### 1) Deterministic first divergence at token 50
+- first token divergence index: `50`
+- first meaningful divergence index: `50`
+- non-incremental path becomes more `[STREAMING_PAD]`-heavy after divergence.
+
+Artifacts:
+- `perf/audio_runs/trace-noninc-vs-inc-20260209T151236Z/comparison.json`
+- `perf/audio_runs/trace-noninc-vs-inc-20260209T154656Z/comparison.json`
+- `perf/audio_runs/trace-noninc-vs-inc-20260209T154656Z/focus_pairwise.json`
+
+### 2) Decoder sliding window is not primary cause
+A sweep over decoder `sliding_window` (`128, 512, 2048, 8192, 16384`) keeps first divergence pinned at `50`.
+Small windows degrade quality further, but do not move divergence onset.
+
+### 3) Stage localization
+- Mel parity: effectively equal.
+- Conv parity: `forward_conv` vs concatenated `forward_conv_step` is exactly equal through position `133`.
+  - first conv nonzero mismatch at `134` (later than divergence trigger region).
+- Transformer path: full-sequence vs cached-history diverges from layer 0 with history present.
+
+### 4) Decoder path appears consistent given input embeddings
+`generate_nonincremental` == decode-from-nonincremental-embeds replay, while decode from incremental embeds differs with first divergence at token 50.
+
+### 5) Reproduced on original-author commit
+Commit `e6d193e85e84e30f26e370c66973ce287b8a9d57`:
+- 120s: first divergence index `50`, token norm ~`0.254473`
+- 20s: first divergence index `50`, token norm ~`0.065637`
+
+Artifacts:
+- `perf/audio_runs/commit-compare-e6d193e-20260209T000000Z/comparison.json`
+- `perf/audio_runs/commit-compare-e6d193e-20s-20260209T000000Z/comparison.json`
+
+## Ruled Out / Lower-Probability Causes
+- Async scheduling race (`mx.async_eval`) as primary cause.
+- STFT/mel mismatch as primary cause.
+- Conv-step equivalence as primary cause.
+- Decoder cache window wrap as primary cause for token-50 onset.
+
+## Likely Root Cause Class
+Encoder transformer full-sequence attention path (`encoder.__call__`) and cached incremental path (`forward_transformer(..., cache=...)`) are not numerically/semantically equivalent with history, causing early embedding drift and autoregressive argmax flip at token 50.
+
+## Suggested Maintainer Actions
+1. Treat incremental encoder path as correctness baseline for file decoding.
+2. Add a regression check: first divergence index vs incremental reference on 120s fixture should be `None` (or within strict tolerance).
+3. Investigate encoder full-vs-cached attention equivalence in layer 0 with history present (mask alignment / cached-history semantics in MLX SDPA).
+4. Optionally reintroduce a faster batch path only if it matches incremental-reference behavior on the same trace metrics.
diff --git a/perf/audio_runs/commit-compare-e6d193e-20260209T000000Z/comparison.json b/perf/audio_runs/commit-compare-e6d193e-20260209T000000Z/comparison.json
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+{
+  "commit": "e6d193e85e84e30f26e370c66973ce287b8a9d57",
+  "clip_seconds": 120,
+  "encoder_sliding_window": 750,
+  "downsample_factor": 4,
+  "decoder_sliding_window": 8192,
+  "encode_shapes": {
+    "non_incremental": [
+      1548,
+      3072
+    ],
+    "incremental": [
+      1548,
+      3072
+    ]
+  },
+  "timing_seconds": {
+    "encode_non_incremental": 1.6301077500684187,
+    "encode_incremental": 14.639893083949573,
+    "decode_non_incremental": 15.363023707992397,
+    "decode_incremental": 16.155508458032273
+  },
+  "divergence": {
+    "first_token_divergence_index": 50,
+    "token_levenshtein": 384,
+    "token_norm_vs_incremental": 0.2544731610337972,
+    "non_incremental_len": 1509,
+    "incremental_len": 1509
+  },
+  "embed_diff": {
+    "global_max_abs": 4.375,
+    "global_mean_abs": 0.038422007113695145,
+    "first_pos_max_abs_gt_1e-2": 2,
+    "first_pos_max_abs_gt_1e-1": 18,
+    "first_pos_max_abs_gt_1": 48,
+    "max_abs_at_88": 0.126953125
+  }
+}
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diff --git a/perf/audio_runs/commit-compare-e6d193e-20s-20260209T000000Z/comparison.json b/perf/audio_runs/commit-compare-e6d193e-20s-20260209T000000Z/comparison.json
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--- /dev/null
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@@ -0,0 +1,38 @@
+{
+  "commit": "e6d193e85e84e30f26e370c66973ce287b8a9d57",
+  "clip_seconds": 20,
+  "encoder_sliding_window": 750,
+  "downsample_factor": 4,
+  "decoder_sliding_window": 8192,
+  "encode_shapes": {
+    "non_incremental": [
+      298,
+      3072
+    ],
+    "incremental": [
+      298,
+      3072
+    ]
+  },
+  "timing_seconds": {
+    "encode_non_incremental": 0.27456287504173815,
+    "encode_incremental": 2.430891291005537,
+    "decode_non_incremental": 2.217908125021495,
+    "decode_incremental": 2.190300542046316
+  },
+  "divergence": {
+    "first_token_divergence_index": 50,
+    "token_levenshtein": 17,
+    "token_norm_vs_incremental": 0.06563706563706563,
+    "non_incremental_len": 259,
+    "incremental_len": 259
+  },
+  "embed_diff": {
+    "global_max_abs": 1.125,
+    "global_mean_abs": 0.013421893119812012,
+    "first_pos_max_abs_gt_1e-2": 2,
+    "first_pos_max_abs_gt_1e-1": 18,
+    "first_pos_max_abs_gt_1": 48,
+    "max_abs_at_88": 0.126953125
+  }
+}
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