One API vs OpenHands
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Self-hosted gateway that exposes many LLM providers through one OpenAI-style API with key management.
Open source · MIT
A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud.
The short answer
Choose One API if you need…
- Developers who want one OpenAI-compatible endpoint for several model providers
- Small teams or groups who need to issue and limit API keys to members
- Operators who want load balancing or retries across multiple provider channels
- People comfortable running a Docker container or a Go binary on a server
Choose OpenHands if you need…
- Developers who want coding agents running on a server while their laptop is off
- Teams that want a shared agent server for tasks like code review or dependency updates
- People who want to connect agents to Slack, GitHub, or Linear through automations
- Users who want to choose their own LLM provider
Side-by-side
| One API | OpenHands | |
|---|---|---|
| Type | App | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 37.3k | 92.5k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Run with Docker | Install with a package manager |
| Main language | JavaScript | TypeScript |
| Last code update | 10 months ago | 4 days ago |
What each one is
One API
One API is a self-hosted web service that sits between your apps and many large language model providers such as OpenAI, Azure, Claude, Gemini and DeepSeek. Clients send requests in the standard OpenAI API format, and One API translates them to each provider. It also includes a web admin panel for issuing tokens, setting quotas, and managing channels.
OpenHands
Agent Canvas is a self-hosted control center for AI coding agents. You start conversations with agents and set up automations, such as generating reports that publish to Slack or breaking GitHub issues into tasks. It runs on your own machine by default and can also connect to agents running in Docker, on virtual machines, or on OpenHands Cloud or Enterprise infrastructure. It can run the open source OpenHands agent or third-party agents such as Claude Code, Codex, and Gemini CLI.
Best for
One API
- Developers who want one OpenAI-compatible endpoint for several model providers
- Small teams or groups who need to issue and limit API keys to members
- Operators who want load balancing or retries across multiple provider channels
- People comfortable running a Docker container or a Go binary on a server
OpenHands
- Developers who want coding agents running on a server while their laptop is off
- Teams that want a shared agent server for tasks like code review or dependency updates
- People who want to connect agents to Slack, GitHub, or Linear through automations
- Users who want to choose their own LLM provider
Strengths
One API
- Single OpenAI-format interface across many listed providers
- Ships as a single executable or Docker image, per the README
- Includes token, quota, channel, and user-group management in one admin UI
OpenHands
- Self-hosted, so you control where agents run and where your work is stored
- Supports several agents and backends from one frontend
- Released under the MIT license with a large public community (about 92,000 stars)
Not ideal for
One API
- Users who only call one provider and do not need a gateway, since it adds a service to run
- Anyone who needs a fully managed hosted service, because this is software you deploy and maintain yourself
- Those who cannot verify compliance with local AI service rules, since the README asks users to follow OpenAI terms and applicable law and warns about unregistered public services in China
OpenHands
- People who need strong isolation by default: the quickstart without a sandbox gives the agent full access to your filesystem
- Non-technical users who are not comfortable with Node.js, npm, Docker, or the command line
- Anyone who needs a fully hosted service with no setup, since the README centers on self-hosting
Trade-offs
One API
- The README warns to change the default root password (123456) immediately after first login
- Some features such as model mapping can change request bodies and drop fields not yet supported
- High concurrency requires setting SQL_DSN, so a production setup likely involves a database beyond the default
OpenHands
- Running without a sandbox gives the agent full access to your filesystem, so the Docker options need careful setup
- Multiple features depend on configuring backends, LLM keys, and integrations, which takes effort
- The README is truncated and does not fully document security hardening or every integration; see the linked docs
Getting started
One API
Run with SQLite using Docker
docker run --name one-api -d --restart always -p 3000:3000 -e TZ=Asia/Shanghai -v /home/ubuntu/data/one-api:/data justsong/one-apiOpenHands
Install globally with npm (no sandbox)
npm install -g @openhands/agent-canvasStart the full local stack
agent-canvasFrequently asked questions
What is the difference between One API and OpenHands?
One API: Self-hosted gateway that exposes many LLM providers through one OpenAI-style API with key management. OpenHands: A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud. One API suits developers who want one openai-compatible endpoint for several model providers, while OpenHands suits developers who want coding agents running on a server while their laptop is off.
Are One API and OpenHands free?
One API: Free and open source. OpenHands: Free and open source.
Is One API or OpenHands more popular?
OpenHands has more GitHub stars (92.5k) than One API (37.3k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to One API and OpenHands?
Other options people compare them with include LibreChat, FlareSolverr, LlamaGPT, draw-a-ui, CLIProxyAPI.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.