The fastest, cheapest, most efficient open-source agent harness. Run more than 500 agents on a $10 VPS.
A desktop app for people. A Rust library for developers.
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> [!NOTE] > 🎉 Within one week of launch, OpenHuman became the **number one trending repository on GitHub** for nine days in a row. > **Early beta.** OpenHuman is under active development, so expect rough edges. --- ## Install The easiest way is to download the desktop app from [tinyhumans.ai/openhuman](https://tinyhumans.ai/openhuman?utm_source=github&utm_medium=readme) or the [latest release](https://github.com/tinyhumansai/openhuman/releases/latest). There is a `.dmg` for macOS, an `.msi` or `.exe` for Windows, and a `.deb` or `.AppImage` for Linux. Prefer the terminal? The install script picks the right package for your system, checks its checksum and installs it: ```bash # macOS and Linux curl -fsSL https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.sh | bash ``` ```powershell # Windows (PowerShell) irm https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.ps1 | iex ``` To preview what the macOS and Linux script would do, end the command with `bash -s -- --dry-run`. Other options and troubleshooting are in [INSTALL.md](./INSTALL.md). --- ## Why OpenHuman? Most agent harnesses run one heavy process per agent and resend a big prompt on every call. OpenHuman does the same work with far less. It is the only feature-rich open-source harness built for large fleets of agents: 500 of them fit on a $10 server.
FastBenchmark results · Cold-start numbers Finishes coding tasks in about 20 seconds, the fastest of seven AI agent tools we tested. Starts up in a tenth of a second. |
CheapCost and token data · How compression works Uses 2.6x fewer tokens than the typical agent tool, and had the lowest total bill in our test. |
Efficient at scaleFleet measurements · Methodology Uses about 8x less memory and CPU than the typical agent tool. Run more than 500 agents on a $10 server. |
Built for developersRust quickstart · Embedding guide · Examples Use it as a Rust library: call an agent like any other function, or run a whole fleet from one small server. |
Same prompt, Same model, Same reasoning side by side: "Write me a story about agent harnesses in the form of an anime story, write it into an HTML page and open it for me." OpenHuman finished in 20s, using 15k tokens for $0.0054. Hermes took 9min 40s, using 37k tokens for $0.0082.
--- ## Major innovations Most agent harnesses are a simple loop: send everything to the model, wait, repeat. That works for one agent, but it gets slow and expensive quickly, and it falls apart when you run hundreds. OpenHuman rethinks the parts that cost the most: how much text the AI has to read, how it finds the right tool, how features load, and how much machine the whole thing needs. The six ideas below are where the speed and savings above come from. Each card links to the docs if you want the details.
RLM token compressionBuilt on Recursive Language Models. Large tool results get compressed before the AI reads them. For very large ones, the AI gets a handle it can search instead of reading it all. Nothing is thrown away. |
Jev: instant, accurate tool searchJev is a tiny model that finds the right tool out of 1,215. The right one is in its top picks 86.8% of the time, against 70.5% for keyword search. |
Unified Rust busEvery feature, like search, documents or voice, plugs into one Rust bus, an idea borrowed from the Linux system bus. A feature loads only when needed, and if one gets stuck, the rest keep working. |
Deeply integrated memoryHow memory works · Memory engines Memory comes built in. Before every turn, OpenHuman picks out only what matters, within a token budget, and hands it to the AI with citations. It works out of the box, and you can swap in a different memory engine with a setting. |
Instant browser and desktop controlBrowser and computer control · Jev The agent uses a real browser and your desktop apps. Jev picks each click from the buttons on screen, with no screenshots. It stops before any payment. |
A programmable Rust coreThe whole harness is compiled Rust in one process, so it starts in a tenth of a second and stays light: 68 MB at peak on our coding tasks. The same core is a library. Call an agent from your own Rust code, or run hundreds of them side by side on one small server. |
