whisper-large-v3-q4

whisper-large-v3-q4 is an MLX-ready Whisper speech-to-text checkpoint derived from openai/whisper-large-v3 for local transcription on Apple Silicon.

Intended use

• Local speech-to-text transcription on Apple Silicon
• Batch or interactive audio transcription experiments
• Multilingual ASR workflows when supported by the upstream Whisper checkpoint

Out of scope

• Safety-critical decisions without domain expert review
• Claims of benchmark superiority not backed by published evaluation data
• Non-MLX runtime guarantees; this card documents the shipped HF checkpoint, not every possible serving stack
• Speaker diarization, clinical interpretation, or audio enhancement

Training and conversion metadata

Parameter	Value
Repository	LibraxisAI/whisper-large-v3-q4
Base model	openai/whisper-large-v3
Task	automatic-speech-recognition
Library	transformers
Format	MLX / Apple Silicon checkpoint
Quantization	Q4
Architecture	Not declared in config
Model files	1
Config model_type	whisper

This card only reports metadata present in the Hugging Face repository, existing card frontmatter, or public config files. Missing benchmark, dataset, or training-run details are left explicit rather than reconstructed.

Usage

Python

import mlx_whisper

result = mlx_whisper.transcribe(
    "audio.wav",
    path_or_hf_repo="LibraxisAI/whisper-large-v3-q4",
)
print(result["text"])

Notes

• Use local audio files supported by mlx_whisper.
• For long recordings, split audio into manageable chunks before transcription.

Example output

No public sample output is currently declared for this checkpoint. Run the usage example above against your own prompt or audio/image input to inspect behavior.

Quantization notes

Aspect	Original/base checkpoint	This checkpoint
Lineage	openai/whisper-large-v3	LibraxisAI/whisper-large-v3-q4
Runtime target	Upstream runtime format	MLX on Apple Silicon
Quantization	Base precision or upstream-declared format	Q4
Published quality delta	Not declared in public metadata	Not declared in public metadata

Limitations

• No public benchmarks for this checkpoint are declared in the model metadata.
• No public benchmark claims are made by this card unless listed in the frontmatter.
• Validate outputs on your own domain data before relying on this checkpoint.
• Memory use and speed depend heavily on the exact Apple Silicon generation, unified-memory size, and prompt length.

License

mit. Check the upstream/base model license as well when a base model is declared.

Citation

@misc{libraxisai-whisper-large-v3-q4,
  title = {whisper-large-v3-q4},
  author = {LibraxisAI},
  year = {2026},
  howpublished = {\url{https://huggingface.co/LibraxisAI/whisper-large-v3-q4}},
  note = {MLX checkpoint published by LibraxisAI}
}

Inference tested on

LibraxisAI/mlx-batch-server

Related

• Base model: openai/whisper-large-v3

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