HiveBearHiveBear

Free, open-source, self-hosted AI that actually fits your machine. A P2P mesh of neighbors pooling everyday hardware to run big local AI models together. Written in Rust, powered by the hive.

Product

  • Download
  • Documentation
  • FAQ
  • About

Run a model

  • Run Llama 3 70B
  • Run DeepSeek R1
  • Run Qwen 2.5 72B
  • Run Mistral 7B
  • All models →

Compare

  • HiveBear vs Ollama
  • HiveBear vs LM Studio
  • HiveBear vs exo
  • HiveBear vs Jan.ai

Community

  • GitHub
  • Discussions
  • Community hub
PawPaw the bear, chilling

Built with Rust. MIT License. © 2026 BeckhamLabs.

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Your download is starting

macOS (Intel) · HiveBear-x64.dmg. Didn't start? Click here.

Keep this page open — the next two minutes are below.

Install on macOS

  1. 1

    Open the .dmg and drag HiveBear into Applications

    It's in your Downloads folder.

  2. 2

    Open HiveBear — macOS will stop it once

    HiveBear isn't notarized by Apple yet, so macOS says it “can't verify” the app. Click Done (not Move to Trash).

  3. 3

    Allow it in System Settings

    Open System Settings → Privacy & Security, scroll to “HiveBear was blocked”, click Open Anyway and confirm with your password. You only do this once.

    Prefer the terminal? This does the same thing:

    $ xattr -dr com.apple.quarantine /Applications/HiveBear.app
  4. Skip the prompts entirely: installing from the terminal doesn't trigger Gatekeeper.
    $ curl -fsSL https://hivebear.com/install.sh | sh -s -- --desktop

Your first five minutes

Install the suggested model

HiveBear checks your hardware and picks a model that fits. One click, usually a 1–5 GB download.

Chat, fully offline

Everything runs on your machine. Nothing leaves it.

Benchmark your machine

30 seconds. Share it anonymously and help people with the same hardware pick the right model.

See the leaderboard →

Optional: a free account puts your name on the benchmark leaderboard and links your devices. HiveBear works fully without one. Create an account

Stuck? Ask on GitHub Discussions — we read everything.