# Phonon-1 Benchmark Scores & Performance

> Phonon-1 has Fermion speech evaluation results. Voice evidence is display-only and does not produce a text-model score.

Canonical page: https://benchlm.ai/models/phonon-1

Last updated: September 30, 2026

## Model Details

| Property | Value |
|----------|-------|
| Creator | Fermion Research |
| Source Type | Open Weight |
| Reasoning Type | Non-Reasoning |
| Context Window | N/A |
| Official model card | [Fermion Research model documentation](https://huggingface.co/FermionResearch/Phonon-1) |
| Overall Score | Not scored (voice evidence only) |
| Overall Rank | Unranked |

## Family & Coverage

- Family: Phonon-1
- Variant: base
- Benchmarks covered: 0 of 486
- Coverage note: Speech and voice results appear below; no weighted text-model benchmark rows are stored.

## Speech and voice evidence

[Phonon-2 launch evaluation](/voice-benchmarks/phonon-2-launch-evaluation)

Fermion ran Phonon-2, Phonon-1, and Parakeet Redux with the Open ASR Leaderboard code on full test sets. The other accuracy rows are leaderboard figures quoted by Fermion, without independent re-verification here. Some model cards report different runs; those values are not mixed into this comparison. Voxtral's download size is an estimate at 16 bits. Throughput includes log-mel processing and excludes model load; batch-128 GPU results are separate from single-stream results. The Mac runtime comparison uses 20 dictations totaling 797 seconds at each runtime's defaults. Download size does not measure runtime memory. These results do not enter text-model or voice-agent rankings.

| Metric | Result |
| --- | --- |
| Seven-set mean WER | 6.56% |
| LibriSpeech clean WER | 2.11% |
| LibriSpeech other WER | 5.03% |
| AMI WER | 10.31% |
| Earnings-22 WER | 12.34% |
| GigaSpeech WER | 8.73% |
| SPGISpeech WER | 3.67% |
| VoxPopuli WER | 3.73% |
| Download | 415 MB |

Fermion-run; Fermion launch table retrieved September 30, 2026. Lower WER is better; throughput excludes model load.

- [Evaluation source](https://www.fermionresearch.com/research/phonon-2/)

Open English speech recognition weights under Apache 2.0, based on Qwen3-ASR 0.6B and trained at 2.4 bits per weight. The Phonon-2 launch reports a seven-set evaluation; Phonon-1's original eight-benchmark model-card results use a different evaluation and are not substituted here.

## Other Fermion Research Models

- [Phonon-2](/models/phonon-2) - Score: not computed