Nativ vs Mirai
Side-by-side comparison for macOS
Nativ
6.0Run AI models locally
Mirai
7.0Inference engine for AI models
| Metric | Nativ | Mirai |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 6.0 | 7.0 |
| 30-day Installs | 117 | 132 |
| 90-day Installs | 262 | 187 |
| 365-day Installs | 262 | 240 |
| Version | 0.4.1 | 0.6.9 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | — | 14.8K |
| GitHub Forks | — | 2.5K |
| Open Issues | — | 296 |
| License | — | AGPL-3.0 |
| Language | — | Kotlin |
| Last GitHub Commit | — | 2y ago |
| First Seen | Aug 26, 2026 | Jun 1, 2026 |
Reviews
Nativ
Nativ is a macOS app designed to run AI models locally, offering a native GUI built with Rust. It provides an efficient way to execute AI tasks without relying on cloud services, benefiting developers and data enthusiasts focused on local AI processing.
Nativ allows users to run AI models locally on their macOS devices.
Pros
- + Efficient local AI model execution without cloud dependency
- + Native GUI built with Rust for better performance and security
- + Potential for cost savings by avoiding cloud computing expenses
Cons
- - Low adoption as indicated by zero recent installs
- - Early maturity may lead to instability or missing features
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