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LM Studio vs Ollama
Side-by-side comparison for macOS
LM Studio
8.0Discover, download, and run local LLMs
Ollama
8.0Get up and running with large language models locally
| Metric | LM Studio | Ollama |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 8.0 | 8.0 |
| 30-day Installs | 7.1K | 12.4K |
| 90-day Installs | 17.3K | 27.2K |
| 365-day Installs | 40.2K | 55.4K |
| Version | 0.4.12,1 | 0.23.1 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | 136 | 164.8K |
| GitHub Forks | 28 | 14.9K |
| Open Issues | 2 | 2.6K |
| License | MIT | MIT |
| Language | Python | Go |
| Last GitHub Commit | 2y ago | 1mo ago |
| First Seen | Jul 22, 2023 | Dec 18, 2023 |
Reviews
LM Studio
LM Studio simplifies discovering, downloading, and running local large language models, catering to developers and data privacy enthusiasts who prefer on-prem AI solutions.
LM Studio allows users to discover, download, and run local large language models.
Pros
- + Simplifies discovery and management of local LLMs
- + Supports various models and architectures
- + Auto-updates ensure the latest features and bug fixes
Cons
- - Occasional bugs reported by users
- - Primarily suited for technically inclined users
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.