OpenBrowse

The open-source Browser Use Cloud alternative. Self-host AI browser agents on a Raspberry Pi or any VPS, drive them through the same v3 REST API the browser-use-sdk already speaks, and watch every run live in a real browser. Built on top of the Browser Use SDK. It's cheaper, faster, and more reliable than BU Cloud.

openbrowse.co

Benchmarks

Given the same real-world extraction task (a careers page with 14 records behind an embedded, cross-origin board, requiring full schema output):

_{¹ Extracted successfully, though some returned fields (e.g. job seniority) were hallucinated when not shown on the page.}

_{All runs, every model tried, and the task specification.}

Why OpenBrowse over BU Cloud?

_{The full dimension-by-dimension comparison.}

⚡ See it in action

Here's a snippet of our benchmark run, with claude-opus-5 taking agentic actions across parallel tabs while its code streams into a live IDE.

https://github.com/user-attachments/assets/c1330d77-67b6-4a7d-bd43-7cdfa230b9d1

Model providers

Recommended models

1. For most use cases, gpt-5.6-terra { "reasoningEffort": "none" }, gpt-5.6-sol { "reasoningEffort": "none" } and claude-sonnet-5 { "reasoningEffort": "high" } all strike a great balance of reliability, accuracy, and cost.

2. For intense workflows, use claude-opus-5 { "reasoningEffort": "medium" } or gpt-5.6-sol { "reasoningEffort": "none" } — both are great options, but watch out for token burn.

3. On a budget? Use gpt-5.6-luna { "reasoningEffort": "max" } with a tightly focused prompt. It might take a while, and it's more prone to hallucinations (especially with broad prompts), but the actual extractions are still great quality.

Comparisons

The same real-world extraction task (a careers page with 14 records behind an embedded, cross-origin board, full schema output) run against BU Cloud and against OpenBrowse on a Raspberry Pi 5 (16GB) without concurrency, ordered cheapest to most expensive:

_{¹ Extracted successfully, though some returned fields (e.g. job seniority) were hallucinated when not shown on the page.}

OpenAI and Anthropic models are generally at their best at the opposite ends of the reasoning dial. For example, OpenAI's GPT-5.6-Terra performs better with less reasoning, spending less time planning ahead and more time reacting to the page in front of it, while Anthropic's 5-series Claude models lean towards rabbit holes and need reasoning time to refocus on the goal.

Common questions

Quick start

Install OpenBrowse with your favorite package manager:

# uv
uv tool install openbrowse
openbrowse start

# pipx
pipx install openbrowse
openbrowse start

# venv
source <path-to-venv>/bin/activate
pip install openbrowse
openbrowse start

To install from source, clone the repo and use uv directly:

git clone git@github.com:lujstn/openbrowse.git
cd openbrowse
uv sync
uv run openbrowse serve

Then, open http://localhost:8420 in a browser. You'll be guided through everything you need to run OpenBrowse. View the installation guide for more details.

Exposing it to the web

OpenBrowse runs on plain Python + Chromium and can be easily port forwarded. To reach it from outside that box without opening ports, put it behind Tailscale:

# private access from your own devices
tailscale up

# or expose the API publicly over TLS with Tailscale Funnel
sudo tailscale funnel --bg 8420

Features

• v3-compatible REST API: sessions, structured output schemas, cost caps, live URLs.
• Visual, tab-based browsing: parallel foreground tab waves for bulk reads; a code tab shows when the agent runs a script; everything visible over VNC.
• Schema answer store: every write validated live against your JSON Schema, coverage tracked per field, a completeness gate before done, and mark-absent semantics for data a site genuinely does not publish.
• Grounding guards: shell-read detection with automatic in-frame retry, evidence-checked enum writes, URL fields validated as absolute http(s) links at the store boundary, honest failure over invented data.
• Profile import: bring BU Cloud profiles (cookies + localStorage) via CLI or the dashboard.
• Dashboard: live session feed with model reasoning, per-step costs, JSON export (full / steps / output-only), profile management.
• CAPTCHA solving: optional CapSolver integration.
• Multi-provider: Anthropic and OpenAI models behind one API, with per-provider repair layers for each family's failure modes.

Citation

This project is licensed under the MIT License. If you use OpenBrowse as part of your research or project, please cite:

@software{openbrowse2026,
  author = {Johnston Kurilov, Lucas},
  title = {{OpenBrowse}: Self-hosted AI browser agents},
  year = {2026},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.21986248},
  url = {https://github.com/lujstn/openbrowse}
}

built with <з by @lujstn