Comparison
mlx-audio vs TTS
Verdict
Pick mlx-audio when license: mlx-audio is MIT, TTS is MPL-2.0; pick TTS when license: TTS is MPL-2.0, mlx-audio is MIT.
Markdown twin · mlx-audio alternatives · TTS alternatives
GraphCanon updated today
Trust & integrity
| Signal | mlx-audio | TTS |
|---|---|---|
| Maintenance | Very active (1d since push) As of today · github_public_v1 | Dormant (693d 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 | 137 low (137 low) 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.
- TTS
- 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Stars
- mlx-audio
- 7.5k
- TTS
- 46k
Forks
- mlx-audio
- 664
- TTS
- 6.2k
Open issues
- mlx-audio
- 83
- TTS
- 4
Language
- mlx-audio
- Python
- TTS
- Python
Adopt for
- mlx-audio
- -
- TTS
- -
Persona
- mlx-audio
- -
- TTS
- -
Runtime
- mlx-audio
- -
- TTS
- -
License
- mlx-audio
- MIT
- TTS
- MPL-2.0
Last pushed
- mlx-audio
- Jul 10, 2026
- TTS
- Aug 16, 2024
Categories
- mlx-audio
- Model Training, Speech & Audio
- TTS
- Inference & Serving, Model Training, Speech & Audio
Trust and health
Maintenance
- mlx-audio
- Very active (96%)
- TTS
- Dormant (18%)
Days since push
- mlx-audio
- 1d
- TTS
- 693d
Open issues (now)
- mlx-audio
- 83
- TTS
- 4
Owner type
- mlx-audio
- User
- TTS
- Organization
Security scan
- mlx-audio
- No lockfile
- TTS
- 137 low (137 low)
Full report
- mlx-audio
- Trust report
- TTS
- Trust report
Shared compatibility
- Python · mlx-audio: Python runtime · TTS: Python runtime
Choose mlx-audio if…
- License: mlx-audio is MIT, TTS is MPL-2.0.
- Tags unique to mlx-audio: apple-silicon, audio-processing, mlx, multimodal.
- 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 TTS if…
- License: TTS is MPL-2.0, mlx-audio is MIT.
- Tags unique to TTS: deep-learning, glow-tts, hifigan, melgan.
- Also covers Inference & Serving.
- TTS ships Docker support for self-hosted deployment.
When NOT to use TTS
- Last GitHub push was 694 days ago (dormant maintenance, Aug 16, 2024). Validate activity before betting a new project on TTS.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Blaizzy/mlx-audio) · observed Jul 11, 2026
- GitHub forks (Blaizzy/mlx-audio) · observed Jul 11, 2026
- Last push (Blaizzy/mlx-audio) · observed Jul 10, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (coqui-ai/TTS) · observed Jul 11, 2026
- GitHub forks (coqui-ai/TTS) · observed Jul 11, 2026
- Last push (coqui-ai/TTS) · observed Aug 16, 2024
- License file (MPL-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: mlx-audio 7.5k · TTS 46k (synced Jul 11, 2026).
Common questions
- What is the difference between mlx-audio and TTS?
- 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.. TTS: 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production. See the comparison table for live GitHub stats and shared categories.
- When should I choose mlx-audio over TTS?
- Choose mlx-audio over TTS when License: mlx-audio is MIT, TTS is MPL-2.0; Tags unique to mlx-audio: apple-silicon, audio-processing, mlx, multimodal; More recently updated (last pushed Jul 10, 2026).
- When should I choose TTS over mlx-audio?
- Choose TTS over mlx-audio when License: TTS is MPL-2.0, mlx-audio is MIT; Tags unique to TTS: deep-learning, glow-tts, hifigan, melgan; Also covers Inference & Serving; TTS ships Docker support for self-hosted deployment.
- 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 TTS?
- Last GitHub push was 694 days ago (dormant maintenance, Aug 16, 2024). Validate activity before betting a new project on TTS. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is mlx-audio or TTS more popular on GitHub?
- TTS has more GitHub stars (45,737 vs 7,525). Stars measure visibility, not whether either tool fits your constraints.
- Are mlx-audio and TTS open source?
- Yes - both are open-source projects on GitHub (mlx-audio: MIT, TTS: MPL-2.0).
- Where can I find alternatives to mlx-audio or TTS?
- GraphCanon lists graph-backed alternatives at mlx-audio alternatives and TTS alternatives (mlx-audio markdown twin, TTS 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 TTS?
- mlx-audio: Very active. TTS: Dormant. 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 TTS?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mlx-audio trust report; TTS trust report.