MemOS vs ollama
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| MemOS | ollama | |
|---|---|---|
| Tagline | MemOS: Self-evolving memory OS for LLM & AI Agents | Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. |
| Stars | 10k | 176k |
| Forks | 920 | 17k |
| Open issues | 180 | 3.4k |
| Language | TypeScript | Go |
| License | Apache-2.0 | MIT |
| Last pushed | Jul 7, 2026 | Jul 7, 2026 |
| Categories | AI Agents | AI Agents, LLM Frameworks |
MemOS
MemOS is a system designed to provide ultra-persistent memory, hybrid retrieval capabilities, and cross-task skill reuse for language models (LLM) and ai agents, with a claimed 35.24% token savings.
TypeScript
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