LlamaGPT 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
A self-hosted chatbot that runs Llama 2 models locally, so your chats stay on your machine.
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 LlamaGPT if you need…
- People who want a private chatbot and don't want to send prompts to a cloud provider
- Users with a home server running umbrelOS who want a one-click install
- Developers who want a local, OpenAI-style API for testing
- Mac users with Docker who want to try local models
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
| LlamaGPT | OpenHands | |
|---|---|---|
| Type | App | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 10.9k | 92.5k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Clone and build from source | Install with a package manager |
| Main language | TypeScript | TypeScript |
| Last code update | 3 years ago | 4 days ago |
What each one is
LlamaGPT
LlamaGPT is a ChatGPT-style chat interface that runs open Llama 2 and Code Llama models on your own hardware instead of a cloud service. The project says no data leaves your device. It is packaged with Docker, so you start it with a script and then use it in a browser at localhost:3000.
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
LlamaGPT
- People who want a private chatbot and don't want to send prompts to a cloud provider
- Users with a home server running umbrelOS who want a one-click install
- Developers who want a local, OpenAI-style API for testing
- Mac users with Docker who want to try local models
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
LlamaGPT
- Runs locally with no data sent out, as the README states
- Supports several model sizes, from 7B to 70B, plus Code Llama variants
- Offers an OpenAI-compatible API and one-command Docker setup
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
LlamaGPT
- People with limited RAM or no capable CPU or GPU, since the larger models need 6GB to over 40GB of memory per the README table and run slowly on small devices
- Anyone who needs the latest hosted models or top-quality answers, because these are smaller open models and the README does not compare their quality to GPT-4
- Users who need to load their own custom models today, since the README lists that feature as not yet done
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
LlamaGPT
- Speed varies a lot by hardware; the README benchmarks range from 0.9 to 54 tokens per second
- Large models need a lot of memory and disk space
- Custom models and switching models in the UI are still on the roadmap
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
LlamaGPT
Clone the repository
git clone https://github.com/getumbrel/llama-gpt.gitEnter the project folder
cd llama-gptOpenHands
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 LlamaGPT and OpenHands?
LlamaGPT: A self-hosted chatbot that runs Llama 2 models locally, so your chats stay on your machine. OpenHands: A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud. LlamaGPT suits people who want a private chatbot and don't want to send prompts to a cloud provider, while OpenHands suits developers who want coding agents running on a server while their laptop is off.
Are LlamaGPT and OpenHands free?
LlamaGPT: Free and open source. OpenHands: Free and open source.
Is LlamaGPT or OpenHands more popular?
OpenHands has more GitHub stars (92.5k) than LlamaGPT (10.9k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to LlamaGPT and OpenHands?
Other options people compare them with include Ollama, GPT4All, llama.cpp, DB-GPT, LocalAI.
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.