serve vs ollama
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| serve | ollama | |
|---|---|---|
| Tagline | Build multimodal AI applications with cloud-native stack | Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. |
| Stars | 22k | 176k |
| Forks | 2.2k | 17k |
| Open issues | 25 | 3.4k |
| Language | Python | Go |
| License | Apache-2.0 | MIT |
| Last pushed | Mar 24, 2025 | Jul 7, 2026 |
| Categories | Model Training, Inference & Serving, Developer Tools | AI Agents, LLM Frameworks |
serve
Jina-Serve is a framework for building and deploying AI services that support gRPC, HTTP, and WebSockets communication. It offers native support for major ML frameworks, high-performance service design, built-in Docker integration, easy deployment to Jina AI Cloud, and Kubernetes compatibility.
Python
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