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Mirai vs vMLX
Side-by-side comparison for macOS
Mirai
7.0Inference engine for AI models
vMLX
7.5Run local AI models on Apple Silicon
| Metric | Mirai | vMLX |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 7.0 | 7.5 |
| 30-day Installs | 18 | 149 |
| 90-day Installs | 45 | 477 |
| 365-day Installs | 72 | 564 |
| Version | 0.4.7 | 1.6.51 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | 14.8K | 567 |
| GitHub Forks | 2.5K | 66 |
| Open Issues | 296 | 36 |
| License | AGPL-3.0 | Apache-2.0 |
| Language | Kotlin | Python |
| Last GitHub Commit | 1y ago | 3mo ago |
| First Seen | Jun 1, 2026 | Jun 1, 2026 |
Reviews
Mirai
Mirai is an AI inference engine designed to help developers efficiently deploy and run machine learning models on various platforms. It supports cross-platform development and provides tools for on-device processing, making it ideal for developers working on AI applications.
Mirai runs AI models on devices, enabling efficient inference and deployment.
Pros
- + Efficient AI model deployment
- + Cross-platform support
- + Active development community
Cons
- - Confusing name due to Mirai botnet association
- - Potential security concerns
vMLX
vMLX is a tool for running local AI models optimized for Apple Silicon, offering features like disk caching and scheduling. It benefits developers and data scientists working on machine learning projects.
vMLX enables running local AI models on Apple Silicon-based Macs.
Pros
- + Optimized for Apple Silicon for better performance
- + Supports local AI model execution
- + Active development with recent updates
- + Open-source under Apache-2.0 license
- + Features like disk caching enhance reliability
Cons
- - Low recent installs indicating niche adoption
- - Some functionalities are requested but not yet implemented