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How to measure task time for two local Qwen models on your sites with Fast Browser Use

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

Authorization notice. Fast Browser Use is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.

Who it is forA researcher or engineer choosing between a smaller and a larger local model for browser automation on their own hardware.

The problemPublished numbers come from one hardware setup, so you cannot tell how a model performs on your machine and tasks.

The outcomeA set of task times and pass or fail checks for both models that you can compare with the README benchmark tables.

What you need first

  • 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

Steps

  1. Clone the repo with git clone https://github.com/APUS-AI-Lab/fast-browser-use (inferred, check the README)
  2. Install Python 3.12+ and uv, then download both Qwen3.5-9B and Qwen3.5-35B-A3B weights as described in the README Quickstart.
  3. Pick two or three browser tasks, such as the Wikipedia navigation task, and write the strict URL or title check for each.
  4. Run each task three times per model and record the task time, as the README benchmark does with three trials.
  5. Compare your median times with the published tables in docs/performance.md and the telemetry in docs/qwen9b-demo-measurement.json.

Prompt for your agent

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.

Caveat. The published benchmarks come from one NVIDIA RTX PRO 6000 Blackwell workstation, so your timings will differ on other hardware.

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