免费 / 开源由 DeepSeek-V4 与 R1 驱动的高效开源权重与托管推理 AI,token 成本极低。
Dify 记录了 819,691 月访问量,月度环比增长为 -15%,定价为免费增值。Msgmate.io 记录了 0 月访问量,增长率为 0%,定价为付费。
Msgmate.io is the home of Open-Chat Go, a self-hostable, federated chat platform that pairs a Go backend and React frontend with an async worker queue, REST and WebSocket APIs, bots and agents, and a growing set of LLM models and tools. You can chat with models in the browser, through a terminal UI, or by wiring the API into your own messenger and automation stack.
| 维度 / 指标 | ![]() | |
|---|---|---|
| 官方域名 | dify.ai | msgmate.io |
| 定价模式 | 免费增值 | 付费 |
| 月访问量 | 81.97万 (819,691) | 0 (0) |
| 月度环比流量变化 | -14.43万 (-15%) | 0 (0%) |
| 主要市场与份额 | 🇨🇳 中国 (46.7%) | 🌐 全球 (—) |
| 直接访问 / 月 | 47.06万 | 0 |
| 用户评分 | 4.8 | 4.3 |
| 支持的平台 | 网站 | 网站 |

构建、部署并治理可上生产的智能体 AI 工作流
可视化画布把检索、分支、工具调用、人工审核与模型步骤组织成清晰可测的执行路径,便于调试与交接。
通过对话或手动配置创建智能体,赋予其技能、工具与知识,然后发布为应用、嵌入组件或工作流中的可复用节点。
为文档、站点与云盘构建可重复的摄取流程,上线前完成抽取、清洗、分块、索引与检索测试。
模型供应商、工具、数据源与 MCP 集成安装一次即可在工作空间内的所有应用中复用。
Msgmate.io is the home of Open-Chat Go, a self-hostable, federated chat platform that pairs a Go backend and React frontend with an async worker queue, REST and WebSocket APIs, bots and agents, and a growing set of LLM models and tools. You can chat with models in the browser, through a terminal UI, or by wiring the API into your own messenger and automation stack.
Chat with large language models in a federated web app, with the active model shown and selectable - the site currently references cognitivecomputations/dolphin-2.6-mixtral-8x7b.
A REST API and WebSocket interface, plus an interactive OpenAPI reference, let developers build bots, agents and their own clients on top of the platform.
Because Open-Chat Go is open source and self-hostable, you can run the Go backend, async worker queue and React frontend on your own servers. Docs cover flags, environment variables and deployment.
Bots and agents add tools and integrations to the base chat experience, so the assistant can do more than plain conversation.
免费 / 开源由 DeepSeek-V4 与 R1 驱动的高效开源权重与托管推理 AI,token 成本极低。
免费 / 开源在本地或云端运行和构建开源 AI 模型
免费 / 开源在一个简洁快速的工作区与 30+ 主流 AI 模型对话
提供简化的无代码构建工具来部署自定义 AI 代理,但缺乏 Dify 的开源弹性。
免费 / 开源LabEx is a hands-on learning platform for Linux, DevOps, cybersecurity, programming, and data science. Instead of watching videos, learners work inside real online terminals and virtual environments to complete structured labs and build portfolio-ready projects.
免费 / 开源LabEx is a hands-on learning platform for Linux, DevOps, cybersecurity, programming, and data science. Instead of watching videos, learners work inside real online terminals and virtual environments to complete structured labs and build portfolio-ready projects.

免费 / 开源Open WebUI is an open-source, self-hosted AI interface that lets individuals and organizations run any model — local or cloud — inside a workspace they fully control. It ships as a one-command install, supports Ollama, OpenAI-compatible and Anthropic endpoints, and extends through Python tools, functions and pipelines.
免费 / 开源Open WebUI is an open-source, self-hosted AI interface that lets individuals and organizations run any model — local or cloud — inside a workspace they fully control. It ships as a one-command install, supports Ollama, OpenAI-compatible and Anthropic endpoints, and extends through Python tools, functions and pipelines.
免费 / 开源AnythingLLM is a free, open-source AI assistant that runs on your own computer or server: chat with documents, transcribe and summarize meetings, run background jobs, use web search and connect any LLM provider — without accounts, API keys or token limits.
免费 / 开源AnythingLLM is a free, open-source AI assistant that runs on your own computer or server: chat with documents, transcribe and summarize meetings, run background jobs, use web search and connect any LLM provider — without accounts, API keys or token limits.

专项更强Provides advanced programmatic frameworks for document parsing and RAG pipelines, but requires coding instead of visual canvases.
专项更强Provides advanced programmatic frameworks for document parsing and RAG pipelines, but requires coding instead of visual canvases.