需要 Python 3.10 以上,macOS 自带 python3 是 3.9 需先建新版本虚拟环境;Linux 上要先从 CPU wheel 索引装 torch 以跳过 GPU 构建;模型权重需从 Hugging Face 单独下载,phonon serve 默认监听 127.0.0.1:8000。
phonon
fermionresearchApache-2.0活跃维护开源语音识别模型 Phonon-2 和 Phonon-1,提供命令行工具以及 CPU、CUDA 镜像,支持低比特量化和 MLX 加速,方便本地部署语音转文字。
Phonon: open speech recognition models (Phonon-2, Phonon-1) — CLI, CPU and CUDA images
python3.12 -m venv .venv && source .venv/bin/activate
pip install fermion-researchCPU 需 x86-64 支持 SSE4.1 以上或 64 位 Arm 支持 NEON,AVX2、AVX-512 VNNI、AMX 及 Arm dotprod、i8mm 可跑更快内核层;Apple 芯片走 MLX,NVIDIA GPU 走 CUDA 镜像;README 未说明显存要求。
Fermion Research 开源语音识别引擎,命令行转写文件、实时听写麦克风并起 OpenAI 兼容服务
开源语音识别模型 Phonon-2 和 Phonon-1,提供命令行工具以及 CPU、CUDA 镜像,支持低比特量化和 MLX 加速,方便本地部署语音转文字。
核心能力
- 在 Apple 芯片上用 MLX 引擎跑 Phonon 模型
- CPU 覆盖 Linux、Windows、macOS,含 x86-64 与 Arm
- 提供 NVIDIA CUDA 与 CPU 两种 Docker 镜像
- phonon serve 起 OpenAI 兼容 HTTP 接口并支持 WebSocket 流式
- 用 --hotwords 偏向人名和术语,--json 输出词级时间戳
容易踩的坑
- libphonon-android-arm64-v8a-1.1.0libphonon 1.1.0 for Android (arm64-v8a)最新正式版2026-10-28 · 2026-10-28 14:51 UTC
Phonon speech-to-text as one C library for Android: audio in, text out. Runs Phonon-2.5 English, Phonon-2.5 and Phonon-2 from their model files (
model.fermionandconfig.json, inside the.bps.tar.zstfile of each model on Hugging Face). Android 8.0 (API 26) and later, arm64-v8a, 16 KB pages.What's new
- Faster on phones at one and two threads.
- Uses about 40 % less memory on recent phones (Pixel 8 and later, Galaxy S22 and later).
- On phones with fast and slow cores, the library keeps its threads on the fast cores. Set
cpu_policy = PHONON_CPU_OSto leave placement to Android.
In the package
lib/libphonon.so(Armv8.2-A with dotprod) andlib/libphonon-base.so(Armv8.0 NEON); pick one at run time asREADME.txtshows.include/phonon.h,docs/ABI.md,bin/phonon-cli(example),LICENSE,NOTICE,SHA256SUMS.
Transcripts are identical to the previous version. Licence: Apache 2.0 for the library and header; the model weights keep their own licence (CC-BY-4.0).
Checksum (
libphonon-1.1.0-android-arm64-v8a.tar.gz, 431,846 bytes):sha256 6362307831a36ae8726fb22c8be6dcea90c6ab298bf44603b5aefc42012be29f - v0.2.15fermion-research 0.2.152026-10-24 · 2026-10-24 12:17 UTC
查看更新说明
fermion serveon an address other than localhost now requires--api-key.- Phonon models load faster on Apple silicon; long recordings use less memory.
- Containers:
phonon-cpu:2.0.12(amd64 and arm64) andphonon-cuda:1.0.11run this release.phonon-cudastarts much faster and transcribes longer files.
Performance improvements and bug fixes.
pip install -U fermion-research - v0.2.14fermion-research 0.2.142026-10-23 · 2026-10-23 21:24 UTC
查看更新说明
- Fixes a crash when a model is used from two threads at once, or loaded again in the same process.
fermion serveaccepts long recordings as uploads.- Containers:
phonon-cpu:2.0.11(amd64 and arm64) andphonon-cuda:1.0.10run this release.
Performance improvements and bug fixes.
pip install -U fermion-research - v0.2.13fermion-research 0.2.132026-10-23 · 2026-10-23 15:43 UTC
查看更新说明
- Phonon-2.5, speech recognition in 25 languages:
fermion transcribe phonon-2.5 recording.wav. - Phonon-2.5 English:
fermion transcribe phonon-2.5-en recording.wav. - Smaller model downloads for the Phonon models; the same files on disk after unpacking.
Performance improvements and bug fixes.
pip install -U fermion-research - Phonon-2.5, speech recognition in 25 languages:
- v0.2.12fermion-research 0.2.122026-10-20 · 2026-10-20 00:59 UTC
查看更新说明
- Neutrino models load through
transformersexactly as the model cards show, in bfloat16 by default on every device. - The Neutrino-8B Linux runtime adds
--exact, which matches the float32 reference token for token.
Performance improvements and bug fixes.
pip install -U fermion-research - Neutrino models load through
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
Phonon
Phonon is the speech recognition engine from Fermion Research. It runs the Phonon models on Apple silicon through MLX, on CPUs under Linux (x86-64 and Arm), Windows and macOS (Apple silicon and Intel Macs), and on NVIDIA GPUs through the CUDA image. It transcribes files from the command line, transcribes the microphone live, and serves an OpenAI-compatible endpoint. Phonon-2.5 (156 MB download) transcribes 25 languages, Phonon-2.5 English (158 MB) and Phonon-2 (158 MB) are the English models, and Phonon-1 (415 MB), Phonon-1 Big (581 MB) and Phonon-1 Micro (285 MB) also run.
Models
| Model | Download | Weights |
|---|---|---|
Phonon-2.5 (phonon-2.5), 25 languages | 156 MB | huggingface.co/FermionResearch/Phonon-2.5 |
Phonon-2.5 English (phonon-2.5-en) | 158 MB | huggingface.co/FermionResearch/Phonon-2.5-English |
Phonon-2 (phonon-2) | 158 MB | huggingface.co/FermionResearch/Phonon-2 |
Phonon-1 (phonon-1) | 415 MB | huggingface.co/FermionResearch/Phonon-1 |
Phonon-1 Micro (phonon-1-micro) | 285 MB | huggingface.co/FermionResearch/Phonon-1-Micro |
Phonon-1 Big (phonon-1-big) | 581 MB | huggingface.co/FermionResearch/Phonon-1-Big |
Phonon-2 for Core ML (Neural Engine): huggingface.co/FermionResearch/Phonon-2-CoreML · github.com/fermionresearch/phonon-coreml
Accuracy and speed for each model are on its model page (fermionresearch.com/models/phonon-2 and the model cards above).
Install
Python 3.10 or newer (macOS's built-in python3 is 3.9). On a Mac, create a virtual environment with a newer Python first:
python3.12 -m venv .venv && source .venv/bin/activate
pip install fermion-research
Apple silicon (MLX engine)
pip install "fermion-research[mlx]"
Linux, Windows and Intel Mac CPUs. pip install fermion-research is the whole setup. On Linux, install torch from its CPU wheel index first, which skips the GPU build. Intel Macs: CPU engine (Python 3.10 to 3.12).
pip install --no-deps torch --index-url https://download.pytorch.org/whl/cpu # Linux only
pip install fermion-research
Supported CPUs: x86-64 with SSE4.1 or newer and 64-bit Arm with NEON. AVX2, AVX-512 VNNI and AMX processors, and
dotprod and i8mm Arm processors, run faster tiers of the same kernels; processors without them run a slower baseline
tier with the same transcripts. fermion describe shows the features found on your machine and the tier it runs;
docs/cpu.md has the detail.
CPU container (amd64 and arm64)
docker run --rm -v "$PWD":/audio -v phonon-cache:/home/phonon/.cache ghcr.io/fermionresearch/phonon-cpu:2.0.12 transcribe phonon-2.5 /audio/recording.wav
NVIDIA CUDA container
docker run --rm --gpus all -v "$PWD":/audio -v phonon-cache:/home/phonon/.cache ghcr.io/fermionresearch/phonon-cuda:1.0.11 transcribe phonon-2.5 /audio/recording.wav
Run
phonon runs Phonon-2, phonon-1 runs Phonon-1, and fermion <command> <model> runs any model by name. Name the model. Phonon never guesses.
phonon transcribe meeting.wav # transcribe a file with Phonon-2
phonon transcribe meeting.wav --json # the same, as JSON with word timestamps
phonon transcribe meeting.wav --hotwords "Ada, Quillon" # favour names and terms
phonon listen # live microphone transcription (Apple silicon)
phonon serve # OpenAI-compatible HTTP server on 127.0.0.1:8000
fermion transcribe phonon-2 meeting.wav # the same, naming the model
fermion transcribe phonon-2.5 reunion.wav # Phonon-2.5: 25 languages, detected from the audio
fermion transcribe phonon-2.5-en call.wav # Phonon-2.5 English
curl -s http://127.0.0.1:8000/v1/audio/transcriptions \
-F "[email protected]" \
-F "model=phonon-2"
Streaming
phonon serve also transcribes live audio over a WebSocket at /v1/audio/stream. The protocol and a reference client are in
docs/server.md.
Dictation tools
A dictation tool keeps one Phonon server running and sends each recording to it, over a local port or an owner-only Unix socket.
fermion serve phonon-2 --port 8010 --threads 4 # or: phonon serve --port 8010
fermion serve phonon-2 --unix-socket ~/.cache/fermion/phonon.sock # owner-only socket in place of an API key
engine = "whisper"
[whisper]
backend = "remote"
remote_endpoint = "http://127.0.0.1:8010"
remote_model = "phonon-2"
Keeping the server running at login is covered in docs/server.md.
fermion models lists every model with its aliases and marks the ones already on the machine.
Documentation
- docs/cli.md, the command line.
- docs/server.md, the HTTP server and its API.
- docs/hotwords.md, favouring names and terms (hotwords).
- docs/install.md, installation on every platform.
- docs/cpu.md, running on CPUs, no GPU required.
- docs/cuda.md, the NVIDIA CUDA image.
- docs/troubleshooting.md, fixes for common problems.
The CUDA image is built from docker-phonon2/ and the CPU image from docker-cpu-phonon2/.
Licence
The Phonon-2.5, Phonon-2.5 English and Phonon-2 weights are released under CC-BY-4.0. They are a derivative of NVIDIA's parakeet-tdt-0.6b-v3, with the changes listed in the NOTICE file of the weights repository. The Phonon-1 family weights and the command line are released under Apache-2.0, and Phonon-1 is built on Qwen/Qwen3-ASR-0.6B, also under Apache-2.0. See LICENSE and NOTICE.