ollama vs ray
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| ollama | ray | |
|---|---|---|
| Tagline | Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. | Unified framework for scaling AI and Python applications |
| Stars | 176k | 43k |
| Forks | 17k | 7.8k |
| Open issues | 3.4k | 3.5k |
| Language | Go | Python |
| License | MIT | Apache-2.0 |
| Last pushed | Jul 7, 2026 | Jul 7, 2026 |
| Categories | AI Agents, LLM Frameworks | Developer Tools, Inference & Serving, Data & Retrieval, Model Training, LLM Frameworks |
ollama
Ollama is a platform for deploying and interacting with various large language models (LLMs) such as Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, and Gemma on macOS, Windows, Linux, and Docker environments.
Go
ray
Ray is a compute engine that includes a distributed runtime core and libraries tailored for AI tasks like ML training, hyperparameter tuning, reinforcement learning, and serving. It supports data scalability through Datasets, facilitating efficient distribution of datasets across clusters.
Python