Home/Compare/mlx-audio vs faster-whisper

Comparison

mlx-audio vs faster-whisper

Verdict

Pick mlx-audio when tags unique to mlx-audio: apple-silicon, audio-processing, mlx, multimodal; pick faster-whisper when requirements: Requires Python 3.9 or higher.

Markdown twin · mlx-audio alternatives · faster-whisper alternatives

GraphCanon updated today

mlx-audio logo

mlx-audio

Blaizzy/mlx-audio

7.5kpushed Jul 10, 2026
vs
faster-whisper logo

faster-whisper

SYSTRAN/faster-whisper

24kpushed Nov 19, 2025

Trust & integrity

Signalmlx-audiofaster-whisper
Maintenance
Very active (1d since push)
As of today · github_public_v1
Slowing (234d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No criticals
As of today · osv@v1

Tagline

mlx-audio
A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.
faster-whisper
Faster Whisper transcription with CTranslate2

Stars

mlx-audio
7.5k
faster-whisper
24k

Forks

mlx-audio
664
faster-whisper
2.0k

Open issues

mlx-audio
83
faster-whisper
311

Language

mlx-audio
Python
faster-whisper
Python

Adopt for

mlx-audio
-
faster-whisper
A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2.

Persona

mlx-audio
-
faster-whisper
-

Runtime

mlx-audio
-
faster-whisper
-

License

mlx-audio
MIT
faster-whisper
MIT

Last pushed

mlx-audio
Jul 10, 2026
faster-whisper
Nov 19, 2025

Categories

mlx-audio
Model Training, Speech & Audio
faster-whisper
Inference & Serving, Speech & Audio

Trust and health

Maintenance

mlx-audio
Very active (96%)
faster-whisper
Slowing (36%)

Days since push

mlx-audio
1d
faster-whisper
234d

Open issues (now)

mlx-audio
83
faster-whisper
311

Owner type

mlx-audio
User
faster-whisper
Organization

Security scan

mlx-audio
No lockfile
faster-whisper
No criticals

Full report

mlx-audio
Trust report
faster-whisper
Trust report

Shared compatibility

  • Python · mlx-audio: Python runtime · faster-whisper: Python runtime

Choose mlx-audio if…

  • Tags unique to mlx-audio: apple-silicon, audio-processing, mlx, multimodal.
  • Also covers Model Training.
  • More recently updated (last pushed Jul 10, 2026).

When NOT to use mlx-audio

  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

Choose faster-whisper if…

  • Requirements: Requires Python 3.9 or higher.
  • Tags unique to faster-whisper: deep-learning, inference, openai, quantization.
  • Also covers Inference & Serving.
  • A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2.

When NOT to use faster-whisper

  • * When needing to employ FFmpeg directly for audio processing as it does not require FFmpeg installation and relies instead on PyAV.
  • * In environments where additional dependencies from PyAV may introduce complexity or issues.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: mlx-audio 7.5k · faster-whisper 24k (synced Jul 11, 2026).

Common questions

What is the difference between mlx-audio and faster-whisper?
mlx-audio: A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.. faster-whisper: Faster Whisper transcription with CTranslate2. See the comparison table for live GitHub stats and shared categories.
When should I choose mlx-audio over faster-whisper?
Choose mlx-audio over faster-whisper when Tags unique to mlx-audio: apple-silicon, audio-processing, mlx, multimodal; Also covers Model Training; More recently updated (last pushed Jul 10, 2026).
When should I choose faster-whisper over mlx-audio?
Choose faster-whisper over mlx-audio when Requirements: Requires Python 3.9 or higher; Tags unique to faster-whisper: deep-learning, inference, openai, quantization; Also covers Inference & Serving; A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2.
When should I avoid mlx-audio?
Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
When should I avoid faster-whisper?
* When needing to employ FFmpeg directly for audio processing as it does not require FFmpeg installation and relies instead on PyAV. * In environments where additional dependencies from PyAV may introduce complexity or issues.
Is mlx-audio or faster-whisper more popular on GitHub?
faster-whisper has more GitHub stars (24,214 vs 7,525). Stars measure visibility, not whether either tool fits your constraints.
Are mlx-audio and faster-whisper open source?
Yes - both are open-source projects on GitHub (mlx-audio: MIT, faster-whisper: MIT).
Where can I find alternatives to mlx-audio or faster-whisper?
GraphCanon lists graph-backed alternatives at mlx-audio alternatives and faster-whisper alternatives (mlx-audio markdown twin, faster-whisper markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, mlx-audio or faster-whisper?
mlx-audio: Very active. faster-whisper: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for mlx-audio and faster-whisper?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mlx-audio trust report; faster-whisper trust report.