{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/6"}],"enrichment":{"capability":"Runs OpenAI's Whisper speech recognition models on Apple silicon using MLX, with support for models ranging from 39 million to 1.5 billion parameters.","skillfed_tags":["speech-recognition","apple-silicon","offline-inference"],"use_cases":["Transcribe audio files to text on macOS without sending data to external APIs.","Build command-line tools that convert speech recordings (MP3, WAV, etc.) to text files.","Integrate speech-to-text into Python applications with control over model size and precision.","Process audio streams piped from other programs directly into transcription.","Generate word-level timestamps for audio segments to enable precise subtitle generation."],"what_it_does":"mlx-whisper brings OpenAI's Whisper speech recognition to Apple silicon Macs by wrapping the models in MLX, a machine learning framework optimized for Apple hardware. It offers both a command-line interface for simple transcription and a Python API for programmatic use. The package can load models from the Hugging Face Hub or local paths, supporting models at various parameter scales and offering features like word-level timestamps.\n\nThe package depends on torch, mlx, numpy, scipy, and several utility libraries for audio processing and model management. It requires ffmpeg as a system dependency for audio handling. Transcription is performed locally on-device, which means no network calls to external APIs and full control over model selection and quantization.","worth_installing":"Yes, if you are on Apple silicon and need local speech recognition. The package is actively maintained, has low install friction, and MIT licensing poses no restrictions. Verify that torch and mlx dependencies resolve cleanly on your target hardware, and ensure ffmpeg is available before installation."},"id":"mlx-whisper","links":{"html":"https://skillfed.io/packages/mlx-whisper","md":"https://skillfed.io/packages/mlx-whisper.md","pypi":"https://pypi.org/project/mlx-whisper/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-08-29","license_spdx":null,"license_treatment":"permissive","name":"mlx-whisper","python_support":"supports_current","summary":"OpenAI Whisper on Apple silicon with MLX and the Hugging Face Hub"},"popularity":{"monthly_downloads":336970,"position":7453,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.4.3"}