{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "apus-ai-lab-fast-browser-use--benchmark-local-models-on-browser-tasks",
 "repo": "APUS-AI-Lab/fast-browser-use",
 "repo_url": "https://github.com/APUS-AI-Lab/fast-browser-use",
 "repo_slug": "apus-ai-lab-fast-browser-use",
 "title": "Measure task time for two local Qwen models on your sites",
 "page_title": "How to measure task time for two local Qwen models on your sites with Fast Browser Use",
 "summary": "Run the same browser task on Qwen3.5-9B and Qwen3.5-35B-A3B and compare task times and verification results.",
 "who": "A researcher or engineer choosing between a smaller and a larger local model for browser automation on their own hardware.",
 "problem": "Published numbers come from one hardware setup, so you cannot tell how a model performs on your machine and tasks.",
 "outcome": "A set of task times and pass or fail checks for both models that you can compare with the README benchmark tables.",
 "steps": [
  "Clone the repo with `git clone https://github.com/APUS-AI-Lab/fast-browser-use` (inferred, check the README)",
  "Install Python 3.12+ and uv, then download both Qwen3.5-9B and Qwen3.5-35B-A3B weights as described in the README Quickstart.",
  "Pick two or three browser tasks, such as the Wikipedia navigation task, and write the strict URL or title check for each.",
  "Run each task three times per model and record the task time, as the README benchmark does with three trials.",
  "Compare your median times with the published tables in docs/performance.md and the telemetry in docs/qwen9b-demo-measurement.json."
 ],
 "agent_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.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "about 120 minutes",
 "basis": "readme",
 "caveat": "The published benchmarks come from one NVIDIA RTX PRO 6000 Blackwell workstation, so your timings will differ on other hardware.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "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"
 ],
 "risk": "dual-use",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/apus-ai-lab-fast-browser-use/benchmark-local-models-on-browser-tasks/",
 "md": "https://dedupedai.com/use-cases/apus-ai-lab-fast-browser-use/benchmark-local-models-on-browser-tasks/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/apus-ai-lab-fast-browser-use--benchmark-local-models-on-browser-tasks.json",
 "api_version": "v1"
}