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Lorqa/nemotron-3.5-asr-streaming-multilingual-0.6b-coreml
nemotron-3.5-asr-streaming-multilingual-0.6b-coreml is a automatic speech recognition model from Lorqa. Use it when you need speech turned into text. The card lists the license as other.
CoreML build of NVIDIA's Nemotron 3.5 streaming ASR model, used by Lorqa for on-device live captions and audio transcripts on macOS and iOS. Runs on the Apple Neural Engine through the FluidAudio SDK.
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Updated Aug 26, 2026
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From the Hugging Face model README
CoreML build of NVIDIA's Nemotron 3.5 streaming ASR model, used by Lorqa for on-device live captions and audio transcripts on macOS and iOS. Runs on the Apple Neural Engine through the FluidAudio SDK.
Only the multilingual/2240 ms tier — 22 files, ~634 MB.
multilingual/2240ms/
├── encoder.mlmodelc/ # 539 MB
├── decoder.mlmodelc/
├── decoder_joint.mlmodelc/
├── joint.mlmodelc/
├── preprocessor.mlmodelc/
├── metadata.json # prompt_dictionary, lang tag token ids
└── tokenizer.json
Upstream ships 8 bundles (latin / multilingual × 560/1120/2240/4480 ms).
The other seven are deliberately not mirrored here — see below.
The four tiers are not quality levels or versions. They are streaming chunk
lengths: how much audio goes into one forward pass (chunk_mel_frames ×
10 ms hop). All four share the same att_context_size of [42, 13].
Measured on the multilingual bundle (RTFx = audio-seconds per wall-second, higher is better; parenthesised figure is WER, or CER for zh/ja — lower is better):
| Tier | Chinese | Japanese | Multilingual-English |
|---|---|---|---|
| 560 ms | 22 (19.48%) | 21 (14.61%) | 23 (9.15%) |
| 1120 ms | 27 (18.75%) | 26 (13.77%) | 71 (8.64%) |
| 2240 ms ⭐ | 89 (18.57%) | 84 (13.79%) | 80 (8.76%) |
| 4480 ms | 90 (18.05%) | 89 (13.82%) | 78 (8.78%) |
2240 ms is the upstream-recommended default and the only tier that is strong on both axes for CJK. 560 ms falls off the trained attention tiling, so it is worse on accuracy and throughput — it is not a lower-latency trade, it is dominated. Figures are from the upstream model card, not re-measured here.
NVIDIA nemotron-3.5-asr-streaming-0.6b → CoreML export by
FluidInference → this mirror. Weights
are unmodified; this repo exists so Lorqa pins a stable source and users in
mainland China get a fast one. The same content is mirrored on
HuggingFace
and ModelScope.
Licensed under OpenMDW 1.1, following upstream.