ollama
Ollama是一款开源大模型运行管理工具,可在多环境快速部署、运行主流开源大模型,支持对接各类AI应用与开发工具。
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Ollama是一款开源大模型运行管理工具,可在多环境快速部署、运行主流开源大模型,支持对接各类AI应用与开发工具。
- 解决什么问题
- 企业想要自建可控的大模型服务时,往往面临开源模型部署流程复杂、适配成本高、对接现有业务工具难度大的问题,还要承担较高的选型试错成本。
- 适合什么团队
- 适合需要内部部署开源大模型的企业IT团队、AI应用开发团队,以及想要低成本搭建本地AI能力的业务创新团队。
- 使用前注意
- 项目采用MIT开源许可,可自由商用;大模型运行对GPU显存要求随所选模型参数提升而升高,目前社区开放问题较多,可优先参考已有解决方案。
本页用于缩短初步筛选时间,不构成技术、采购或法律结论。 正式使用前请在真实业务数据上验证,并以官方说明与许可证为准。
从官方资料看清能力、部署与采用边界
以下内容依据项目公开 README 或模型卡翻译整理,代码、命令和产品名保持原样。
Ollama 项目导读
项目定位
Ollama的核心定位是降低开源大模型的落地门槛,帮助非专业算法团队也能快速用上开源大模型,无需处理复杂的底层环境配置、模型适配工作。目前它支持Kimi-K2.6、GLM-5.2、MiniMax、DeepSeek、gpt-oss、Qwen、Gemma等多款市场主流开源大模型,业务侧可根据自身需求灵活选择。
核心能力
- 多模型适配:官方提供开箱即用的模型库,覆盖不同参数、不同场景的开源大模型,无需额外做模型适配改造即可直接运行。
- 多形态接入:提供命令行工具、REST API,以及Python、JavaScript等多语言SDK,方便对接企业现有业务系统与工具。
- 丰富生态对接:支持对接各类主流AI相关产品,包括聊天界面、代码编辑器、AI应用开发框架等,无需额外开发即可替换原有工具的大模型供应商。
典型使用方式
1. 直接运行大模型对话
安装完成后,只需执行简单命令即可运行指定大模型并开启对话,例如执行ollama run gemma4即可直接和Gemma 4模型交互,无需其他配置。
2. 对接现有办公/开发工具
可直接将Ollama作为底层大模型底座,对接Claude Code、Codex、Copilot CLI等常用开发工具,也可通过OpenClaw对接企业使用的Slack、企业微信、钉钉等办公沟通工具,搭建企业内部专属AI助手。
3. 作为AI应用开发底座
可对接Dify.AI、LangChain等AI应用开发框架,搭建业务专属的AI应用,例如RAG(检索增强生成,一种让大模型结合企业私有数据回答问题的技术)知识库、智能客服、代码助手等,大幅降低AI应用的开发门槛。
部署要求
Ollama支持多环境部署,适配macOS、Windows、Linux操作系统,也可通过Docker镜像部署,同时支持Google Cloud、Fly.io等云平台部署,也可通过Homebrew、Helm Chart等常用包管理器快速安装。
大模型运行的硬件要求随所选模型的参数大小不同存在差异,小参数模型可在普通办公电脑上运行,大参数模型需要配置对应显存的GPU,企业可根据自身业务需求选择对应模型与硬件配置。
项目维护状态
项目于2023年6月创建,目前仍处于活跃维护状态,未被归档,最近一次代码更新为2026年8月,官方文档完善,社区生态丰富,遇到问题可优先查阅官方文档或社区已有解决方案。
许可证与采用建议
项目采用MIT开源许可,企业可自由使用、修改、分发,无商业使用限制。
对于首次尝试内部部署开源大模型的企业,建议先选择小参数模型在普通设备上测试效果,确认匹配业务需求后再扩容硬件部署到服务器;如果是开发AI应用,可直接对接Ollama的标准API,无需额外投入资源做底层模型适配,降低项目整体成本。
官方资料与来源
- deepseek
- gemma
- gemma3
- glm
- go
- golang
- gpt-oss
- llama
- llama3
- llm
- llms
- minimax
### Infrastructure & Deployment #### Cloud - [Google Cloud](https://cloud.google.com/run/docs/tutorials/gpu-gemma2-with-ollama) - [Fly.io](https://fly.io/docs/python/do-more/add-ollama/) - [Koyeb](https://www.koyeb.com/deploy/ollama) - [Harbor](https://github.com/av/harbor) - Containerized LLM toolkit with Ollama as default backend #### Package Managers - [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/) - [Homebrew](https://formulae.brew.sh/formula/ollama) - [Nix package](https://search.nixos.org/packages?show=ollama&from=0&size=50&sort=relevance&type=packages&query=ollama) - [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama) - [Gentoo](https://github.com/gentoo/guru/tree/master/app-misc/ollama) - [Flox](https://flox.dev/blog/ollama-part-one) - [Guix channel](https://codeberg.org/tusharhero/ollama-guix)
该片段来自项目 README,仅用于初步判断;实际部署请以官方文档为准。
核对上游原始说明节选
Get up and running with Kimi-K2.6, GLM-5.2, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
Ollama
Start building with open models.
Download
macOS
curl -fsSL https://ollama.com/install.sh | shor download manually
Windows
irm https://ollama.com/install.ps1 | iexor download manually
Linux
curl -fsSL https://ollama.com/install.sh | shManual install instructions
Docker
The official Ollama Docker image ollama/ollama is available on Docker Hub.
Libraries
- ollama-python
- ollama-js
Community
- Discord
- 𝕏 (Twitter)
Get started
ollamaYou'll be prompted to run a model or connect Ollama to your existing agents or applications such as Claude Code, OpenClaw, OpenCode , Codex, Copilot, and more.
Coding
To launch a specific integration:
ollama launch claudeSupported integrations include Claude Code, Codex, Copilot CLI, DeepSeek Harness, Droid, and OpenCode.
AI assistant
Use OpenClaw to turn Ollama into a personal AI assistant across WhatsApp, Telegram, Slack, Discord, and more:
ollama launch openclawChat with a model
Run and chat with Gemma 4:
ollama run gemma4See ollama.com/library for the full list.
See the quickstart guide for more details.
REST API
Ollama has a REST API for running and managing models.
curl http://localhost:11434/api/chat -d '{
"model": "gemma4",
"messages": [{
"role": "user",
"content": "Why is the sky blue?"
}],
"stream": false
}'See the API documentation for all endpoints.
Python
pip install ollamafrom ollama import chat
response = chat(model='gemma4', messages=[
{
'role': 'user',
'content': 'Why is the sky blue?',
},
])
print(response.message.content)JavaScript
npm i ollamaimport ollama from "ollama";
const response = await ollama.chat({
model: "gemma4",
messages: [{ role: "user", content: "Why is the sky blue?" }],
});
console.log(response.message.content);Supported backends
- llama.cpp project founded by Georgi Gerganov.
Documentation
- CLI reference
- REST API reference
- Importing models
- Modelfile reference
- Building from source
Community Integrations
Want to add your project? Open a pull request.
Chat Interfaces
Web
- Open WebUI - Extensible, self-hosted AI interface
- Onyx - Connected AI workspace
- LibreChat - Enhanced ChatGPT clone with multi-provider support
- Lobe Chat - Modern chat framework with plugin ecosystem (docs)
- NextChat - Cross-platform ChatGPT UI (docs)
- Perplexica - AI-powered search engine, open-source Perplexity alternative
- big-AGI - AI suite for professionals
- Lollms WebUI - Multi-model web interface
- ChatOllama - Chatbot with knowledge bases
- Bionic GPT - On-premise AI platform
- Chatbot UI - ChatGPT-style web interface
- Hollama - Minimal web interface
- Chatbox - Desktop and web AI client
- chat - Chat web app for teams
- Ollama RAG Chatbot - Chat with multiple PDFs using RAG
- Tkinter-based client - Python desktop client
Desktop
- Dify.AI - LLM app development platform
- AnythingLLM - All-in-one AI app for Mac, Windows, and Linux
- Maid - Cross-platform mobile and desktop client
- Witsy - AI desktop app for Mac, Windows, and Linux
- Cherry Studio - Multi-provider desktop client
- Ollama App - Multi-platform client for desktop and mobile
- PyGPT - AI desktop assistant for Linux, Windows, and Mac
- Alpaca - GTK4 client for Linux and macOS
- SwiftChat - Cross-platform including iOS, Android, and Apple Vision Pro
- Enchanted - Native macOS and iOS client
- RWKV-Runner - Multi-model desktop runner
- Ollama Grid Search - Evaluate and compare models
- macai - macOS client for Ollama and ChatGPT
- AI Studio - Multi-provider desktop IDE
- Reins - Parameter tuning and reasoning model support
- ConfiChat - Privacy-focused with optional encryption
Mobile
- Ollama Android Chat - One-click Ollama on Android
SwiftChat, Enchanted, Maid, Ollama App, Reins, and ConfiChat listed above also support mobile platforms.
Code Editors & Development
- Cline - VS Code extension for multi-file/whole-repo coding
- Continue - Open-source AI code assistant for any IDE
- Void - Open source AI code editor, Cursor alternative
- Copilot for Obsidian - AI assistant for Obsidian
- twinny - Copilot and Copilot chat alternative
- gptel Emacs client - LLM client for Emacs
- Ollama Copilot - Use Ollama as GitHub Copilot
- Obsidian Local GPT - Local AI for Obsidian
- Ellama Emacs client - LLM tool for Emacs
- orbiton - Config-free text editor with Ollama tab completion
- AI ST Completion - Sublime Text 4 AI assistant
- VT Code - Rust-based terminal coding agent with Tree-sitter
- QodeAssist - AI coding assistant for Qt Creator
- AI Toolkit for VS Code - Microsoft-official VS Code extension
- Open Interpreter - Natural language interface for computers
Libraries & SDKs
- LiteLLM - Unified API for 100+ LLM providers
- Semantic Kernel - Microsoft AI orchestration SDK
- LangChain4j - Java LangChain (example)
- LangChainGo - Go LangChain (example)
- Spring AI - Spring framework AI support (docs)
- LangChain and LangChain.js with example
- Ollama for Ruby - Ruby LLM library
- any-llm - Unified LLM interface by Mozilla
- OllamaSharp for .NET - .NET SDK
- LangChainRust - Rust LangChain (example)
- Agents-Flex for Java - Java agent framework (example)
- Elixir LangChain - Elixir LangChain
- [Ollama-rs for Rust