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.

Tested inference path

**Inference for this checkpoint has been tested with LibraxisAI/mlx-batch-server.**
This is the recommended tested path for operator-controlled local inference on Apple Silicon.

Aspect	Status
Tested runtime	LibraxisAI/mlx-batch-server
Target hardware	Apple Silicon
Inference mode	Local / self-hosted
Hugging Face Hosted Inference	Disabled for this repository (inference: false)

This does not claim compatibility with every possible serving stack. It documents the path that has been exercised for this published checkpoint.

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.

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 Apple Silicon generation, unified-memory size, audio duration, and language complexity.

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}
}

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