MLX Speech Models
Collection
Speech AI models for Apple Silicon via MLX. ASR, TTS, VAD, diarization, speaker embedding. • 92 items • Updated • 5
How to use aufklarer/Cohere-Transcribe-2B-MLX-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Cohere-Transcribe-2B-MLX-8bit aufklarer/Cohere-Transcribe-2B-MLX-8bit
MLX weights for Cohere Transcribe 2B, ready for local speech-to-text with speech-swift.
| Parameters | Precision | Sample rate | Languages |
|---|---|---|---|
| 2B | 8-bit affine | 16 kHz | 14 |
| File | Description |
|---|---|
model*.safetensors |
MLX model weights |
config.json |
Model and runtime configuration |
tokenizer.model and tokenizer JSON files |
SentencePiece tokenizer data |
speech transcribe recording.wav --engine cohere --model int8
import CohereTranscribeASR
let model = try await CohereTranscribeModel.load(
"aufklarer/Cohere-Transcribe-2B-MLX-8bit"
)
let text = model.transcribe(
audio: samples,
sampleRate: sourceSampleRate,
language: "en"
)
English FLEURS read speech, 80 utterances (759.56 seconds), Apple M5 Pro:
| Variant | Bundle | WER | Mean RTF | Peak RSS |
|---|---|---|---|---|
| FP16 | 3.85 GiB | 6.178% | 0.0444 | 3,964 MiB |
| INT5 | 1.62 GiB | 6.288% | 0.0150 | 1,776 MiB |
| INT8 | 2.25 GiB | 6.178% | 0.0159 | 2,428 MiB |
These read-speech measurements are not Artificial Analysis Conversational or ElevenLabs Scribe results.
The base model is CohereLabs/cohere-transcribe-03-2026 and is released under Apache 2.0.
8-bit
Base model
CohereLabs/cohere-transcribe-03-2026