cjpais · Oct 6, 2026 · Oct 6, 2026 · Oct 6, 2026 · Oct 6, 2026 · Oct 6, 2026
@@ -23,12 +23,12 @@ C/C++ speech-to-text inference library. Runs diverse STT model families via [GGU
 | Multitalker Parakeet Streaming 0.6B v1 | `multitalker-parakeet-streaming-0.6b-v1` | diarize, streaming, token timestamps | [docs/models/multitalker-parakeet-streaming-0.6b-v1.md](docs/models/multitalker-parakeet-streaming-0.6b-v1.md) |
 | Nemotron 3.5 ASR Streaming 0.6B | `nemotron-3.5-asr-streaming-0.6b` | streaming, token timestamps | [docs/models/nemotron-3.5-asr-streaming-0.6b.md](docs/models/nemotron-3.5-asr-streaming-0.6b.md) |
 | Nemotron Speech Streaming EN 0.6B | `nemotron-speech-streaming-en-0.6b` | streaming, token timestamps | [docs/models/nemotron-speech-streaming-en-0.6b.md](docs/models/nemotron-speech-streaming-en-0.6b.md) |
-| Parakeet | `parakeet-ctc-0.6b`, `parakeet-ctc-1.1b`, `parakeet-primeline`, `parakeet-rnnt-0.6b`, `parakeet-rnnt-1.1b`, `parakeet-tdt-0.6b-v2`, `parakeet-tdt-0.6b-v3`, `parakeet-tdt-1.1b`, `parakeet-tdt_ctc-1.1b`, `parakeet-tdt_ctc-110m`, `parakeet-ultra`, `parakeet-unified-en-0.6b` | streaming, token timestamps | [docs/models/parakeet.md](docs/models/parakeet.md) |
+| Parakeet | `parakeet-ctc-0.6b`, `parakeet-ctc-1.1b`, `parakeet-primeline`, `parakeet-rnnt-0.6b`, `parakeet-rnnt-1.1b`, `parakeet-tdt-0.6b-v2`, `parakeet-tdt-0.6b-v3`, `parakeet-tdt-1.1b`, `parakeet-tdt_ctc-1.1b`, `parakeet-tdt_ctc-110m`, `parakeet-ultra`, `parakeet-unified-en-0.6b`, `orukeet` | streaming, token timestamps | [docs/models/parakeet.md](docs/models/parakeet.md) |
 | Qwen3-ASR | `qwen3-asr-0.6b`, `qwen3-asr-1.7b` | - | [docs/models/qwen3-asr.md](docs/models/qwen3-asr.md) |
 | SenseVoice Small | `sensevoice-small` | - | [docs/models/sensevoice-small.md](docs/models/sensevoice-small.md) |
 | Voxtral (2507) | `voxtral-mini-3b-2507`, `voxtral-small-24b-2507` | translate | [docs/models/voxtral.md](docs/models/voxtral.md) |
 | Voxtral Realtime (2602) | `voxtral-mini-4b-realtime-2602` | streaming | [docs/models/voxtral-realtime.md](docs/models/voxtral-realtime.md) |
-| Whisper | `breeze-asr-25`, `whisper-base`, `whisper-base.en`, `whisper-large`, `whisper-large-v2`, `whisper-large-v3`, `whisper-large-v3-turbo`, `whisper-medium`, `whisper-medium.en`, `whisper-small`, `whisper-small.en`, `whisper-tiny`, `whisper-tiny.en` | segment timestamps, translate | [docs/models/whisper.md](docs/models/whisper.md) |
+| Whisper | `whisper-base`, `whisper-base.en`, `whisper-large`, `whisper-large-v2`, `whisper-large-v3`, `whisper-large-v3-turbo`, `whisper-medium`, `whisper-medium.en`, `whisper-small`, `whisper-small.en`, `whisper-tiny`, `whisper-tiny.en`, `breeze-asr-25` | segment timestamps, translate | [docs/models/whisper.md](docs/models/whisper.md) |
 <!-- /catalog -->
 
 **Speaker diarization models** (no transcription; verified by DER/JER rather than WER):

@@ -0,0 +1,192 @@
+# Orukeet
+
+<!-- catalog:intro -->
+Upstream: [`oruk/orukeet`](https://huggingface.co/oruk/orukeet) at [`b59c13a`](https://huggingface.co/oruk/orukeet/commit/b59c13a).
+
+A tuned version of parakeet-tdt-0.6b-v3 from Oruk AI. Turns speech into
+text in 25 European languages, works offline, and runs as fast as v3. Give
+it a 16 kHz mono WAV and it gives you back text with punctuation and
+capitals. Swap it in anywhere you use v3. Does not stream and does not
+translate.
+<!-- /catalog -->
+
+## What it does
+
+Speech to text in 25 European languages, offline. It is
+`parakeet-tdt-0.6b-v3` with new weights from Oruk AI: same size, same speed,
+same 25 languages, slightly more accurate. If you already run v3, point at
+this file instead and you are done.
+
+It does not stream and it does not translate.
+
+<!-- catalog:pin -->
+Licensed CC-BY-SA-4.0. Ported from upstream commit [`b59c13a`](https://huggingface.co/oruk/orukeet/commit/b59c13a), pinned 2026-10-06. Validated against the NeMo reference at transcribe.cpp commit [`65856fac`](https://github.com/handy-computer/transcribe.cpp/tree/65856fac) on 2026-10-06.
+<!-- /catalog -->
+
+## Download
+
+<!-- catalog:downloads -->
+| Quantization | Download |    Size | WER (LibriSpeech test-clean) |
+| --- | --- | ---: | ---: |
+| F32          | [orukeet-F32.gguf](https://huggingface.co/handy-computer/orukeet-gguf/resolve/main/orukeet-F32.gguf) | 2.51 GB | 1.86% |
+| F16          | [orukeet-F16.gguf](https://huggingface.co/handy-computer/orukeet-gguf/resolve/main/orukeet-F16.gguf) | 1.26 GB | 1.86% |
+| Q8_0         | [orukeet-Q8_0.gguf](https://huggingface.co/handy-computer/orukeet-gguf/resolve/main/orukeet-Q8_0.gguf) |  740 MB | 1.86% |
+| Q6_K         | [orukeet-Q6_K.gguf](https://huggingface.co/handy-computer/orukeet-gguf/resolve/main/orukeet-Q6_K.gguf) |  610 MB | 1.86% |
+| Q5_K_M       | [orukeet-Q5_K_M.gguf](https://huggingface.co/handy-computer/orukeet-gguf/resolve/main/orukeet-Q5_K_M.gguf) |  549 MB | 1.83% |
+| Q4_K_M       | [orukeet-Q4_K_M.gguf](https://huggingface.co/handy-computer/orukeet-gguf/resolve/main/orukeet-Q4_K_M.gguf) |  485 MB | 1.95% |
+<!-- /catalog -->
+
+<!-- catalog:recipe -->
+WER on the full LibriSpeech test-clean split (2,620 utterances), batch size 8, timestamps none, language hint `en`, decoded on cuda. Measured at transcribe.cpp `37273409`.
+<!-- /catalog -->
+
+<!-- catalog:prose field=wer.notes -->
+A bit more accurate than v3 on English and on 20 of the 25 languages.
+parakeet-ultra is more accurate than both on almost everything.
+<!-- /catalog -->
+
+<!-- catalog:accuracy -->
+**FLEURS test**
+
+| Language | Metric |   Q8_0 |
+| --- | --- | ---: |
+| bg       | WER    | 11.14% |
+| cs       | WER    | 10.22% |
+| da       | WER    | 16.58% |
+| de       | WER    |  5.64% |
+| el       | WER    | 33.12% |
+| en       | WER    |  4.43% |
+| es       | WER    |  3.75% |
+| et       | WER    | 15.16% |
+| fi       | WER    | 11.88% |
+| fr       | WER    |  6.17% |
+| hr       | WER    | 11.26% |
+| hu       | WER    | 13.53% |
+| it       | WER    |  3.11% |
+| lt       | WER    | 17.72% |
+| lv       | WER    | 19.53% |
+| mt       | WER    | 17.18% |
+| nl       | WER    |  6.93% |
+| pl       | WER    |  7.35% |
+| pt       | WER    |  4.56% |
+| ro       | WER    | 10.86% |
+| ru       | WER    |  6.70% |
+| sk       | WER    |  8.99% |
+| sl       | WER    | 24.00% |
+| sv       | WER    | 13.26% |
+| uk       | WER    |  6.53% |
+<!-- /catalog -->
+
+## Quick Start
+
+```bash
+cmake -B build
+cmake --build build
+
+build/bin/transcribe-cli \
+  -m models/orukeet/orukeet-Q8_0.gguf \
+  samples/jfk.wav
+```
+
+Audio has to be 16 kHz mono WAV. Convert anything else first:
+
+```bash
+ffmpeg -i input.mp3 -ar 16000 -ac 1 output.wav
+```
+
+It figures out the language on its own. Add `--language de` (or any of the
+25 codes) if you want to force one.
+
+## Performance
+
+Same speed as v3.
+
+### Apple M4 Max
+
+<!-- catalog:perf machine=m4-max -->
+Compute latency (mel + encode + decode), speedup over realtime in parentheses; profile `asr-publication-v2`: mean over 3 iterations after 1 warmup.
+
+| Backend | Sample       |             Q8_0 |           Q4_K_M |
+| ------- | ------------ | ---------------: | ---------------: |
+| Metal   | jfk (11.0s)  |  59 ms (185.68×) |  65 ms (170.12×) |
+| Metal   | dots (35.3s) | 159 ms (221.73×) | 164 ms (215.85×) |
+| CPU     | jfk (11.0s)  |  304 ms (36.17×) |  305 ms (36.03×) |
+| CPU     | dots (35.3s) |  969 ms (36.45×) |  1.03 s (34.29×) |
+
+Apple M4 Max: transcribe.cpp `d91374b3` on 2026-10-06.
+<!-- /catalog -->
+
+### AMD Ryzen 7 PRO 4750U
+
+<!-- catalog:perf machine=ryzen-4750u -->
+Compute latency (mel + encode + decode), speedup over realtime in parentheses; profile `asr-publication-v2`: mean over 3 iterations after 1 warmup.
+
+| Backend | Sample       |            Q8_0 |          Q4_K_M |
+| ------- | ------------ | --------------: | --------------: |
+| Vulkan  | jfk (11.0s)  | 454 ms (24.20×) | 455 ms (24.17×) |
+| Vulkan  | dots (35.3s) | 1.36 s (25.99×) | 1.38 s (25.59×) |
+| CPU     | jfk (11.0s)  | 730 ms (15.07×) | 776 ms (14.18×) |
+| CPU     | dots (35.3s) | 2.90 s (12.17×) | 2.95 s (11.97×) |
+
+AMD Ryzen 7 PRO 4750U (Radeon RADV RENOIR): transcribe.cpp `8bab590e` on 2026-10-06.
+<!-- /catalog -->
+
+Rerun the benchmark yourself:
+
+```bash
+uv run scripts/bench/run.py --profile --models orukeet
+```
+
+## How we checked it
+
+Compared tensor by tensor against NeMo running Oruk's own `.nemo` file,
+using the same tolerances as v3. Everything matches and the test transcript
+is identical. Batches of 2, 4 and 8 give the same text as one at a time.
+
+| Field | Value |
+| --- | --- |
+| Reference | NeMo, `oruk/orukeet` `orukeet-v0.1.0.nemo` |
+| Dump script | `scripts/dump_reference_parakeet_nemo.py` |
+| Manifest | `tests/golden/parakeet/orukeet.manifest.json` |
+| Tolerances | `tests/tolerances/parakeet.json` |
+| Command | `uv run scripts/validate.py all --family parakeet --variant orukeet --model models/orukeet/orukeet-v0.1.0.nemo` |
+
+## Build it yourself
+
+```bash
+# get the source checkpoint
+hf download oruk/orukeet orukeet-v0.1.0.nemo --local-dir models/orukeet
+
+# convert to F32 GGUF
+uv run --project scripts/envs/parakeet \
+  scripts/convert-parakeet.py models/orukeet/orukeet-v0.1.0.nemo \
+    models/orukeet/orukeet-F32.gguf --repo-id oruk/orukeet
+
+# make the smaller files
+uv run scripts/quantize-all.py models/orukeet/orukeet-F32.gguf
+
+# check it against NeMo
+uv run scripts/validate.py all --family parakeet --variant orukeet \
+  --model models/orukeet/orukeet-v0.1.0.nemo
+
+# measure WER
+uv run scripts/wer/ingest.py librispeech
+uv run scripts/wer/run.py \
+  --model models/orukeet/orukeet-F32.gguf \
+  --manifest samples/wer/librispeech-test-clean.manifest.jsonl \
+  --out reports/wer/orukeet-F32.librispeech-test-clean.b1.jsonl
+uv run scripts/wer/score.py reports/wer/orukeet-F32.librispeech-test-clean.b1.jsonl
+```
+
+Oruk also ships a `transcribe-cpp/orukeet-Q8_0.gguf` in their own repo.
+It was made with this same converter and works too; ours is just rebuilt
+from the F32 so all the sizes come from one place.
+
+## Limits
+
+- No streaming.
+- No translation.
+- Timestamps are per token, not per word.
+- Licence is CC-BY-SA-4.0. The rest of the parakeet family is CC-BY-4.0.
+  If you make a derivative of the weights, it has to carry the same licence.
+- Long files go through in one pass. Nothing cuts them up for you.
@@ -6,8 +6,9 @@ of three decoder heads — TDT (transducer with a duration prediction
 head), classical RNN-T, or CTC — and a TDT+CTC hybrid that ships both
 heads in one checkpoint. All variants take 16 kHz mono PCM through a
 mel frontend; English-only across the family, except
-`parakeet-tdt-0.6b-v3`, Moondream's post-trained `parakeet-ultra` and the
-German fine-tune `parakeet-primeline`, which cover 25 European languages.
+`parakeet-tdt-0.6b-v3`, Moondream's post-trained `parakeet-ultra`, Oruk's
+retune `orukeet` and the German fine-tune `parakeet-primeline`, which
+cover 25 European languages.
 
 For the architecture deep-dive, validation contract, and porting notes,
 see the family doc at
@@ -24,6 +25,9 @@ Most users want one of three:
   and on every FLEURS language. A drop-in replacement for
   `parakeet-tdt-0.6b-v3`, which remains available.
   See [parakeet-ultra.md](parakeet-ultra.md) for how it segments long audio.
+- **Multilingual, alternative → `orukeet`.** Oruk AI's retune of v3. Same
+  size and speed, a bit more accurate than v3, less accurate than
+  `parakeet-ultra`. CC-BY-SA-4.0 weights. See [orukeet.md](orukeet.md).
 - **German → `parakeet-primeline`.** primeLine's German fine-tune of
   v3. Same size and speed; tuned for German while keeping the other 24
   v3 languages usable.
@@ -54,12 +58,13 @@ WER is on LibriSpeech test-clean for the **Q8_0** preset, measured by
 transcribe.cpp's WER pipeline. See each per-variant doc for the full
 quant matrix and the comparison to NVIDIA's self-reported numbers.
 
-<!-- catalog:family variants=parakeet-tdt-0.6b-v2,parakeet-ultra,parakeet-tdt-0.6b-v3,parakeet-primeline,parakeet-tdt-1.1b,parakeet-tdt_ctc-110m,parakeet-tdt_ctc-1.1b,parakeet-rnnt-0.6b,parakeet-rnnt-1.1b,parakeet-ctc-0.6b,parakeet-ctc-1.1b,parakeet-unified-en-0.6b -->
+<!-- catalog:family variants=parakeet-tdt-0.6b-v2,parakeet-ultra,parakeet-tdt-0.6b-v3,orukeet,parakeet-primeline,parakeet-tdt-1.1b,parakeet-tdt_ctc-110m,parakeet-tdt_ctc-1.1b,parakeet-rnnt-0.6b,parakeet-rnnt-1.1b,parakeet-ctc-0.6b,parakeet-ctc-1.1b,parakeet-unified-en-0.6b -->
 | Variant                    | Params | Languages                  | Q8_0 size | Benchmark                    |  Q8_0 | Capabilities                | Doc |
 | --- | ---: | --- | ---: | --- | ---: | --- | --- |
 | `parakeet-tdt-0.6b-v2`     |   618M | en                         |    730 MB | LibriSpeech test-clean (WER) | 1.69% | token timestamps            | [parakeet-tdt-0.6b-v2.md](parakeet-tdt-0.6b-v2.md) |
 | `parakeet-ultra`           |   627M | 25 languages + auto-detect |    740 MB | LibriSpeech test-clean (WER) | 1.80% | token timestamps            | [parakeet-ultra.md](parakeet-ultra.md) |
 | `parakeet-tdt-0.6b-v3`     |   627M | 25 languages + auto-detect |    740 MB | LibriSpeech test-clean (WER) | 1.94% | token timestamps            | [parakeet-tdt-0.6b-v3.md](parakeet-tdt-0.6b-v3.md) |
+| `orukeet`                  |   627M | 25 languages + auto-detect |    740 MB | LibriSpeech test-clean (WER) | 1.86% | token timestamps            | [orukeet.md](orukeet.md) |
 | `parakeet-primeline`       |   627M | 25 languages + auto-detect |    740 MB | FLEURS de (WER)              | 5.98% | token timestamps            | [parakeet-primeline.md](parakeet-primeline.md) |
 | `parakeet-tdt-1.1b`        |   1.1B | en                         |   1.27 GB | LibriSpeech test-clean (WER) | 1.38% | token timestamps            | [parakeet-tdt-1.1b.md](parakeet-tdt-1.1b.md) |
 | `parakeet-tdt_ctc-110m`    |   114M | en                         |    135 MB | LibriSpeech test-clean (WER) | 2.43% | token timestamps            | [parakeet-tdt_ctc-110m.md](parakeet-tdt_ctc-110m.md) |

@@ -197,6 +197,28 @@ uv run --project scripts/envs/parakeet-kestrel scripts/wer/run_reference_parakee
 | Speaker diarization | n/a | n/a | n/a | OUT OF SCOPE — not a diarizer | SKIP — not exposed by runtime |
 | Translation | n/a | n/a | n/a | OUT OF SCOPE — not advertised | SKIP — not exposed by runtime |
 
+### orukeet (oruk/orukeet)
+
+Weights-only fine-tune of `parakeet-tdt-0.6b-v3` (Oruk AI, r3 checkpoint).
+Half of the encoder's 9-tap depthwise conv taps are frozen fitted Gabor
+values, stored as ordinary F32 conv weights; architecture, tokenizer and
+frontend are byte-for-byte v3, so no runtime work. Reference is NeMo on
+the `.nemo` archive (the publisher's benchmark pipeline), same env as v3.
+License is CC-BY-SA-4.0, not CC-BY-4.0. Intake:
+`reports/porting/parakeet/orukeet/intake.json`.
+
+| Capability | Mode | Command / test | Expected observable | Target | Status |
+|---|---|---|---|---|---|
+| Transcribe | explicit en | `build/bin/transcribe-cli -m models/orukeet/orukeet-F32.gguf --language en samples/jfk.wav` | English transcript with PnC; LibriSpeech test-clean WER within Stage 7 band of the NeMo oracle | MUST PASS | PASS — jfk byte-equal to NeMo (validate.py compare 18/18 within the finalized parakeet tolerances, transcript exact); LibriSpeech test-clean gate in Stage 7 |
+| Transcribe | auto | `build/bin/transcribe-cli -m models/orukeet/orukeet-F32.gguf samples/jfk.wav` | English transcript, no hint | MUST PASS | PASS — no-hint jfk byte-equal to NeMo |
+| Transcribe | explicit non-English (de/ru/uk clips) | `… --language de samples/german.wav` | transcript in source language with correct script | MUST PASS | PASS — german.wav identical with and without --language de; ru-short / uk-short correct Cyrillic transcripts |
+| Language detection | auto, non-English | `build/bin/transcribe-cli -m models/orukeet/orukeet-F32.gguf samples/ru-short.wav` (no `--language`) | Russian transcript without a hint; same dispatcher path as v3 | MUST PASS | PASS — ru-short / uk-short / german transcribed in-language with no hint (same dispatcher path as v3) |
+| Offline batch | batch | `uv run scripts/batch_parity.py --model <gguf> --list <list.txt> --batch-sizes 2,4,8 --backend cpu` | per-item transcripts equal to serial | MUST PASS | PASS — text byte-equal serial vs 2/4/8 on 7 clips incl. dots (35 s), CPU (golden tests/golden/batch/orukeet.cpu.json, list tests/golden/batch/orukeet.list). product-names.wav (56 s) flips one near-tie token ('QuidQuil' vs 'Quid Quill') at batch 4/8 in a mixed-length batch; parakeet-tdt-0.6b-v3 Q8_0 shows the identical flip on the same clip, so it is a pre-existing runtime property of the family on long padded clips, not this checkpoint, and the clip is excluded from the golden |
+| Timestamps (token/word/segment) | output | `… --timestamps word samples/jfk.wav` | monotonic word times, same TDT duration math as v3 | MUST PASS | PASS — 22 monotonic word spans on jfk, same TDT duration math as v3 |
+| Streaming | streaming | n/a (offline full-context model, `streaming: false`) | n/a | OUT OF SCOPE — no streaming training | SKIP — not exposed by runtime (offline-only model) |
+| Speaker diarization | n/a | n/a | n/a | OUT OF SCOPE — not a diarizer | SKIP — not exposed by runtime |
+| Translation | n/a | n/a | n/a | OUT OF SCOPE — not advertised | SKIP — not exposed by runtime |
+
 ## Open decisions before Stage 3 (convert)
 
 These decisions block converter design for the new variants and should

@@ -133,3 +133,4 @@ cache to mis-index.
   - **TDT global symbol budget** (`stt.parakeet.tdt.symbol_budget="global"`; ref `ParakeetTdt.generate_encoded`): one budget of `max_symbols * T_valid` steps, blank+duration-0 advances one frame, no per-frame cap.
   - **VAD head + long-form segmenter** (`vad.{proj,ctx,out}`, `stt.parakeet.vad.*`, `stt.parakeet.segmenter.*`; ref `vad.py`, `segment.py`, `asr/audio.py` `AudioChunks.chunks`): `build_vad_graph` (subsampler -> proj 1x1 + SiLU -> ctx k=5 + SiLU -> out 1x1 -> sigmoid) per 120 s scan block with per-block mel normalization; host `longform::pause_segments` (float64, ties-to-even round); `run_longform` decodes each segment like a short clip and stitches (space-joined text, timestamps shifted by segment start and clamped to its end, one result segment per decoded segment). Gate: `vad.b<k>.{mel,pre_encode,proj,ctx,prob}`, `vad.prob`, `longform.segments` (exact), `seg.<j>.enc.{mel.in,final}`, stitched transcript exact, word timestamps.
   - **Correctness regime**: `TRANSCRIBE_NO_FLASH=1` via manifest `cpp_env` (flash casts the rel-pos score bias to F16).
+- **`orukeet`** (Oruk AI, reference NeMo): weights-only fine-tune of `parakeet-tdt-0.6b-v3`. Identical geometry, KVs, tokenizer and frontend (24 layers, d_model=1024, n_mels=128, `use_bias=false`, TDT head, pred_n_layers=2, SPM 8192+blank byte-identical to v3). 12,288 of the 24,576 encoder depthwise-conv taps are frozen fitted Gabor values stored as ordinary F32 conv weights, so the forward map is v3's with no deltas; the only converter change is the `orukeet` VARIANT_PROFILES entry (`stt.variant=tdt-0.6b-orukeet`, cc-by-sa-4.0). Validated with the finalized family tolerances unchanged (18/18 on jfk, transcript exact).