An actually robust browser agent powered by local LLM?

Reddit r/LocalLLaMA / 3/26/2026

💬 OpinionSignals & Early TrendsTools & Practical Usage

Key Points

  • A Reddit user asks whether anyone has built a truly robust “browser agent” that runs with a local LLM, avoiding cloud dependence for greater control.
  • They report that using OpenClaw with a local Qwen 3.5 397B (quantized) plus vision has been unreliable, with navigation stalling or dropping mid-request.
  • The user also struggles to set up the workflow where the agent feeds webpage snapshots back into the model to guide subsequent actions.
  • The post seeks practical community advice on what approaches or tooling make local, vision-capable browser agents work more reliably.

Has anyone figured out an actually robust browser agent powered by a local LLM? As a layperson I’ve tried using openclaw powered by local LLM, but it’s just so… buggy and complicated? I’ve been trying to avoid cloud providers and go local only, just to have as much freedom and control as possible.

I’m running Qwen 3.5 397b q4 (it’s slow mind you), trying to get it to do some browser navigation for basically tinkering and fun. I thought that with its vision capabilities and relative intelligence from its large parameter size it would be competent at browsing through the web and completing tasks for me. But it’s been really clunky, dropping or stalling on requests midway, and trying to get openclaw to actually feed the snapshot it takes of webpages to help guide its next step just doesn’t seem easy at all to set up.

Was wondering what others have found helpful to make this type of capability work?

submitted by /u/Diligent-Culture-432
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