Ollama vs Swama
Side-by-side comparison for macOS
Ollama
8.0Get up and running with large language models locally
Swama
8.0Machine-learning runtime
| Metric | Ollama | Swama |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 8.0 | 8.0 |
| 30-day Installs | 11.9K | 58 |
| 90-day Installs | 27.3K | 279 |
| 365-day Installs | 55.7K | 540 |
| Version | 0.23.1 | 2.1.1 |
| Auto-updates | Yes | No |
| Deprecated | No | No |
| GitHub Stars | 164.8K | 506 |
| GitHub Forks | 14.9K | 24 |
| Open Issues | 2.6K | 31 |
| License | MIT | MIT |
| Language | Go | Swift |
| Last GitHub Commit | 1mo ago | 1mo ago |
| First Seen | Dec 18, 2023 | Jun 23, 2025 |
Reviews
Ollama
Ollama enables users to run large language models locally, offering a powerful tool for developers and data scientists. It supports various models and hardware, including AMD GPUs, making it versatile for different computing needs.
Runs large language models locally on your machine.
Pros
- + Enables local running of large language models for privacy and bandwidth efficiency.
- + Supports multiple models and hardware, including AMD GPUs, broadening its accessibility.
- + Active development and strong community support enhance reliability and future potential.
Cons
- - Niche appeal, primarily targeting developers and data scientists familiar with local AI setups.
- - Setup and management of models may be complex for less technical users.
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