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license: apache-2.0
base_model: Qwen/Qwen3-ASR-0.6B
base_model_relation: quantized
language:
- en
library_name: mlx
pipeline_tag: automatic-speech-recognition
tags:
- mlx
- apple-silicon
- speech-to-text
- asr
- stt
- low-bit
- ternary
- quantization-aware-training
- on-device
- streaming
metrics:
- wer
---
# Phonon-1 Micro
Phonon-1 Micro is an open speech recognition model for English, the smallest
build of the Phonon-1 family. It downloads in 285 MB, runs on a laptop or a
datacenter GPU, and beats Moonshine base on all eight benchmarks below. It was
trained at 2.4 bits per weight from the start.
## Benchmarks
| Benchmark | Phonon-1 (415 MB) | **Phonon-1 Micro (285 MB)** | Parakeet-0.6B 4-bit (637 MB) | Moonshine base (248 MB) | Whisper large-v3-turbo (1,619 MB) | Whisper small (967 MB) | wav2vec2-large (1,262 MB) | Qwen3-ASR teacher (1,569 MB) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|
| LibriSpeech test-clean | 2.640 | **3.002** | 2.186 | 3.417 | 2.10 | 3.4† | 2.8† | 2.235 |
| LibriSpeech test-other | 5.699 | **6.511** | 3.937 | 8.262 | 4.07 | 7.6† | 6.3† | 4.618 |
| TED-LIUM | 3.421 | **3.878** | 2.829 | 5.272 | — | — | — | 2.889 |
| SPGISpeech | 4.163 | **4.858** | 4.104 | 5.731 | 2.79† | — | 13.31† | 3.074 |
| VoxPopuli | 8.394 | **9.177** | 6.345 | 10.470 | 11.22† | — | — | 7.151 |
| GigaSpeech | 11.396 | **11.882** | 9.614 | 12.114 | 8.52† | — | — | 9.321 |
| Earnings-22 | 12.571 | **14.771** | 11.190 | 17.872 | 11.07† | — | 36.28† | 11.188 |
| AMI | 13.084 | **14.094** | 12.723 | 17.790 | 15.16† | — | — | 12.560 |
| Macro (eight benchmarks) | 7.67 | **8.52** | 6.62 | 10.1 | — | — | — | 6.63 |
Word error rate, lower is better. Unmarked cells: measured by us — full test
sets, Whisper English text normalizer, greedy decoding. † = published figure
(model card, paper, or the Open ASR Leaderboard). Dash = no comparable
measurement.
## Run it
```bash
pip install fermion-research
fermion transcribe --model FermionResearch/Phonon-1-Micro recording.wav
```
Or serve an OpenAI-compatible endpoint:
```bash
fermion serve --model FermionResearch/Phonon-1-Micro
curl -s http://127.0.0.1:8000/v1/audio/transcriptions \
-F "file=@recording.wav" \
-F "model=FermionResearch/Phonon-1-Micro"
```
The same weights run on a Mac (via MLX), on an NVIDIA GPU, or on a plain CPU;
the runtimes and Docker images are in the [GitHub repo](https://github.com/fermionresearch/phonon).
## License
**Apache License 2.0** for the weights and the [command line](https://pypi.org/project/fermion-research/). Base model: [`Qwen/Qwen3-ASR-0.6B`](https://huggingface.co/Qwen/Qwen3-ASR-0.6B), Apache-2.0.
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