OmO vs Ollama

Side-by-side comparison of two AI agent tools

Short answer

  • Ollama is growing faster: +2,499 GitHub stars in the last 30 days vs +1,005 for OmO.
  • Pick OmO for: omO: Just type "mass ulw" keyword with your prompt. Pick Ollama for: get up and running with Kimi-K2.5, GLM-5, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.

From GitHub data refreshed daily.

O
OmOopen-source

OmO: Just type "mass ulw" keyword with your prompt. Now you are the master of graph engineering.

Ollamaopen-source

Get up and running with Kimi-K2.5, GLM-5, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.

Metrics

OmOOllama
Stars69.8k182.1k
Star velocity /mo1.0k2.5k
Commits (90d)9.4k297
Releases (6m)1010
Overall score0.91053512934996320.8565267401746319

Pros

    • +完全本地运行，确保数据隐私和安全，无需将敏感信息发送到外部服务器
    • +支持广泛的开源模型生态，包括最新的 Kimi-K2.5、GLM-5、DeepSeek 等前沿模型
    • +丰富的集成生态系统，可与 Claude Code、OpenClaw 等工具连接，快速构建跨平台 AI 应用

    Cons

      • -依赖本地计算资源，运行大型模型需要较高的 CPU/GPU 和内存配置
      • -模型推理速度受限于本地硬件性能，可能不如云端专用硬件快
      • -需要手动管理模型版本更新和依赖关系

      Use Cases

        • •企业级私有部署，在内网环境中运行大语言模型，确保敏感数据不外泄
        • •开发者工具集成，通过 Claude Code 等编码助手在本地环境中获得 AI 代码建议
        • •多平台聊天机器人开发，使用 OpenClaw 将本地模型部署到 Slack、Discord 等通讯平台
        View OmO DetailsView Ollama Details

        FAQ

        Which is more popular, OmO or Ollama?
        Ollama has more GitHub stars (182,051 vs 69,754).
        Which is more actively developed, OmO or Ollama?
        OmO had more commits in the last 90 days (9,367 vs 297).
        Should I use OmO or Ollama?
        Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.