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What you can do with Fast Browser Use

Fast Browser Use is a local-first browser automation engine and agent skill that uses open Qwen3.5 models to pick page actions from visible elements.

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APUS-AI-Lab/fast-browser-use on GitHub

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Authorization notice. This tool is dual-use. Only use it on software, sites and systems you own or have explicit permission to test, and follow the relevant licenses and terms of service.

What do you want to do?

3 use cases

  • Check a web settings form saves correctly, offline

    Fill and save a settings form in a local browser run, then confirm the saved message and page state.

    View prompt
    Use the fast-browser-use repo at <repo path> to fill and save the settings form at <form URL> with the values in <values file>. Return the execution trace and whether the saved confirmation text matches <expected text>. Verify the page with the --expect-text assertion before reporting success.

  • Give a coding agent a fast local browser for page tasks

    Let Claude Code, Codex or Cursor handle planning while a local engine handles clicks, selects and scrolls.

    View prompt
    Using the fast-browser-use skill in <repo path>, complete the browser task <task description> on <start URL>. Return the step-by-step execution trace and the final page URL and title. Verify the final URL matches <expected URL> before marking the task done.

  • Measure task time for two local Qwen models on your sites

    Run the same browser task on Qwen3.5-9B and Qwen3.5-35B-A3B and compare task times and verification results.

    View prompt
    In the fast-browser-use repo at <repo path>, run the task <task name> three times each on Qwen3.5-9B and Qwen3.5-35B-A3B. Return a table of task times and whether the final URL and title matched <expected values>. Verify that every run used local inference only before reporting results.

How to use Fast Browser Use

  1. Check you have what it needs: Linux, Windows or macOS with Python 3.12+; uv (https://docs.astral.sh/uv/getting-started/installation/); Local Qwen3.5-9B or Qwen3.5-35B-A3B model weights, run through MLX or PyTorch (CUDA or CPU).
  2. Open APUS-AI-Lab/fast-browser-use on GitHub and read the README and license.
  3. Clone the repo with git clone https://github.com/APUS-AI-Lab/fast-browser-use (inferred, check the README)
  4. Install the prerequisites listed in the README Quickstart: Python 3.12+ and uv.
  5. Download the Qwen3.5-9B weights and set up the engine as described in the README Quickstart section.
  6. Follow the Agent Skill Setup section if you want Claude Code, Codex or Cursor to call the engine.

These steps come from our top use case, Check a web settings form saves correctly, offline, which also has a copy-paste agent prompt.

Fast Browser Use alternatives · Best AI repos for Software and DevOps

About this repo

Requirements

  • Linux, Windows or macOS with Python 3.12+
  • uv (https://docs.astral.sh/uv/getting-started/installation/)
  • Local Qwen3.5-9B or Qwen3.5-35B-A3B model weights, run through MLX or PyTorch (CUDA or CPU)
  • Optional: Node
  • Host agent such as Claude Code, Codex, or Cursor, if you want the agent skill
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Questions about Fast Browser Use

What is Fast Browser Use?

Fast Browser Use is a local-first browser automation engine and agent skill that uses open Qwen3.5 models to pick page actions from visible elements. It is an open-source project on GitHub: https://github.com/APUS-AI-Lab/fast-browser-use.

Who is Fast Browser Use for?

Developers and AI agent users who want fast, offline browser automation that runs on their own machine and works with Claude Code, Codex, or Cursor.

What can I do with Fast Browser Use?

3 use cases so far, for example: Check a web settings form saves correctly, offline; Give a coding agent a fast local browser for page tasks; Measure task time for two local Qwen models on your sites. Each has steps and a copy-paste agent prompt.

What do I need to run Fast Browser Use?

Linux, Windows or macOS with Python 3.12+; uv (https://docs.astral.sh/uv/getting-started/installation/); Local Qwen3.5-9B or Qwen3.5-35B-A3B model weights, run through MLX or PyTorch (CUDA or CPU); Optional: Node.

What are alternatives to Fast Browser Use?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is Fast Browser Use safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.