Mirai vs Swama
Side-by-side comparison for macOS
Mirai
7.0Inference engine for AI models
Swama
8.0Machine-learning runtime
| Metric | Mirai | Swama |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 7.0 | 8.0 |
| 30-day Installs | 19 | 35 |
| 90-day Installs | 50 | 120 |
| 365-day Installs | 50 | 544 |
| Version | 0.3.9 | 2.2.0 |
| Auto-updates | Yes | No |
| Deprecated | No | No |
| GitHub Stars | 14.8K | 506 |
| GitHub Forks | 2.5K | 24 |
| Open Issues | 296 | 31 |
| License | AGPL-3.0 | MIT |
| Language | Kotlin | Swift |
| Last GitHub Commit | 1y ago | 3mo ago |
| First Seen | Jun 1, 2026 | Jun 23, 2025 |
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
Swama
Swama is a high-performance machine learning runtime for macOS, offering efficient inference for large language models with a native Swift implementation. It benefits developers and ML enthusiasts by providing a fast and scalable solution for model execution.
Swama provides a runtime environment for executing machine learning models, particularly large language models, on macOS systems using Swift.
Pros
- + High-performance inference engine for macOS
- + Native Swift implementation for seamless integration
- + Active development and updates
Cons
- - No auto-update feature
- - Limited model support as per current issues
- - Some open issues indicating ongoing development needs