Orukeet: pricing, features, alternatives

Orukeet is a 25-language speech recognizer from Oruk AI, built on NVIDIA Parakeet TDT 0.6B v3. The repo Oruk-AI/orukeet is MIT code, created 2026-09-09, language Python. Weights and fitted kernels are CC BY-SA 4.0. On 2026-09-12 GitHub listed 30 stars and 1 fork. The Hugging Face card showed 13 likes and 2,444 downloads in the last month. r/LocalLLaMA had "Orukeet, new ASR model based on Parakeet" on the hot RSS the same day.

Compare Whisper V3 if you wanted OpenAI's MIT open-weight family, YouTube Transcript if you needed captions from a URL, or Nex-N2.5-mini if you wanted a multimodal agent instead of ASR.

Key Features

Frozen Gabor half: card says it keeps Parakeet's 627,008,134 parameters and 24-layer FastConformer, then replaces half of the encoder's temporal depthwise filters with 12,288 fitted, frozen Gabor kernels. Native exports store those taps as ordinary F16 convolution weights.
First-party WER vs Parakeet (NeMo greedy-batch TDT, same recordings): LibriSpeech test-clean 1.46% vs 1.53%, test-other 2.86% vs 3.14%, FLEURS English 3.82% vs 4.28%, FLEURS 25-language pooled 9.85% vs 11.01% (10.6% relative). Card says it wins 61 of 74 tested splits.
Four formats from r3 (031c8ddab484): NeMo source, native Q8, native F16, ONNX INT8 for sherpa-onnx. OpenWhispr 1.10.0 ships Orukeet as its recommended local model.
Installer: orukeet install --device auto picks Metal on Apple silicon, CUDA on NVIDIA, or CPU. Python 3.12+.

Limitation: 30 stars is a day-three heat signal, not an audit. Final adaptation and checkpoint selection use LibriSpeech test-other, the same split in the WER table. We did not rerun the 74 splits. Native response is text plus window times; no diarization, emotion, or speaker labels.

Specs

Item	Value	Source
Parameters	627,008,134 (Parakeet retained)	HF card
Code / weights	MIT / CC BY-SA 4.0	same card, 2026-09-12
Languages	25 (FLEURS set)	HF `cardData.language`
Likes / last-month downloads	13 / 2,444	HF API, 2026-09-12
GitHub stars	30	GitHub API, 2026-09-12
Software price	$0 code and weights	MIT + CC BY-SA 4.0

Use Cases

Local transcription on Apple silicon or a CUDA box, including OpenWhispr's local picker (Oruk → Orukeet).
People comparing Parakeet TDT 0.6B v3 who want the Gabor-frozen checkpoint, not a from-scratch ASR.
r/LocalLLaMA readers who saw the hot-list title.

If you needed a hosted API default, start with Whisper V3 only after you confirm it is still the open repo you meant, not a billed SKU.

Getting Started

Open oruk/orukeet or the local transcription guide.
python -m pip install the v0.1.1 wheel from GitHub Releases, then orukeet install --device auto.
Load installation.json and call Orukeet(...).transcribe("recording.wav").
Or pick Local → Oruk → Orukeet inside OpenWhispr 1.10.0.

First-party resource: the model card and oruk.ai.

Frequently Asked Questions

Is this NVIDIA Parakeet?

It starts from Parakeet TDT 0.6B v3 and freezes fitted Gabor kernels. NVIDIA attribution stays on the weights (CC BY-SA 4.0).

Can I skip NeMo?

Yes. Native Q8/F16 and the sherpa-onnx INT8 archive do not need NeMo. The card's WER table is NeMo FP32/BF16, not the native runtime.

Why is test-other in both training and the scoreboard?

The card says the last 168 AdamW updates and checkpoint selection use LibriSpeech test-other. Read that as a construction choice, not a held-out audit.

Alternatives

Whisper V3: OpenAI MIT open-weight family.
YouTube Transcript: pull captions from a video URL, not a local ASR.
Nex-N2.5-mini: agent checkpoint, not speech-to-text.

Tips

Keep the worker loaded across files. Reload cost is not in the WER table.
Pin revisions. NeMo/native files use 555136b50265a132d4cea0d35560c26fc4f657ab; ONNX uses a different commit.
Do not paste the 10.6% relative FLEURS drop as a product SLA. It is one pooled first-party comparison.

Orukeet is the CC BY-SA Parakeet fork r/LocalLLaMA linked on 2026-09-12. Start at the Hugging Face card, then decide whether Whisper already covers the languages you need.