← Browse all apps Developer Tools Developer Tools
Ollama vs EXO
Side-by-side comparison for macOS
Ollama
8.0Get up and running with large language models locally
EXO
8.0Run AI models locally across multiple devices
| Metric | Ollama | EXO |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 8.0 | 8.0 |
| 30-day Installs | 14.4K | 446 |
| 90-day Installs | 35.7K | 508 |
| 365-day Installs | 76.9K | 508 |
| Version | 0.31.1 | 1.0.71 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | 164.8K | 45.1K |
| GitHub Forks | 14.9K | 3.2K |
| Open Issues | 2.6K | 242 |
| License | MIT | Apache-2.0 |
| Language | Go | Python |
| Last GitHub Commit | 3mo ago | 1mo ago |
| First Seen | Dec 18, 2023 | Jun 2, 2026 |
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.
EXO
EXO is a tool that enables running AI models locally across multiple devices, making it ideal for developers and AI enthusiasts who need cross-device support. Its unique ability to distribute AI processing efficiently across devices is a key feature.
EXO allows users to run AI models locally on multiple devices.
Pros
- + High popularity indicated by extensive GitHub engagement.
- + Cross-device functionality for efficient AI model execution.
- + Licensed under Apache-2.0, promoting open-source adoption.
Cons
- - Low recent installs suggest limited adoption.
- - High number of open issues may indicate ongoing development or instability.