We got local models to triage the OpenClaw repo for FREE!*
We're on a journey to advance and democratize artificial intelligence through open source and open science. Back to Articles a]:hidden"> We got local models to triage the OpenClaw repo for FREE! * Published June 22, 2026 Update on GitHub Upvote - Onur Solmaz osolmaz Follow ben burtenshaw burtenshaw Follow shaun smith evalstate Follow Pedro Cuenca pcuenq Follow Lysandre lysandre Follow *Free as in beer, excluding the cost of electricity, and assuming you already own the hardware June 2026 will go down as the moment that people realized closed models can be taken away.
Key Takeaways
- With the removal of Anthropic's latest flagship model Claude Fable 5 fresh in memory, one can see why it is more important than ever to own your AI stack and be able to run models locally, especially if you are building your business on top of AI.
In that light, we wanted to share how we use local models like Gemma and Qwen in an agent harness, to run classification tasks[^1].
- OpenClaw gets hundreds of issues and PRs every day, which need to be triaged, prioritized and routed to maintainers.
I, Onur, am working to make local models work well with OpenClaw.
- This would batch issues over longer periods, so we would be trading real-time notifications for delayed processing.
If I were to run this on a local model on the hardware I already have up and running, I would not only have near-instantaneous notifications, I would also be able to do it for free (or rather, for the cost of electricity).
- For the local model choices, we tested and .
With performance optimizations, both can generate hundreds of tokens per second locally.
- For that reason, we use instead of : a restricted -like shell that only allows read-only operations ( , , , , etc.
Stats & Key Facts
- #* Published June 22, 2026 Update on GitHub Upvote - Onur Solmaz osolmaz Follow ben burtenshaw burtenshaw Follow shaun smith evalstate Follow Pedro Cuenca pcuenq Follow Lysandre lysandre Follow *Free as in beer, excluding the cost of electricity, and assuming you already own the hardware June 2026 will go down as the moment that people realized closed models can be taken away.
With the removal of Anthropic's latest flagship model Claude Fable 5 fresh in memory, one can see why it is more important than ever to own your AI stack and be able to run models locally, especially if you are building your business on top of AI. In that light, we wanted to share how we use local models like Gemma and Qwen in an agent harness, to run classification tasks[^1]. This approach is different from using a model like BERT for classification.
A local model in an agent harness like Pi can be used in tandem with structured outputs, to assign labels. We chose this approach because we already had local models and the harness on hand, and have conviction that similar setups will increase in popularity as local models improve in capability. [^2] Our starting point was open source contributions in the OpenClaw repo.
OpenClaw gets hundreds of issues and PRs every day, which need to be triaged, prioritized and routed to maintainers. I, Onur, am working to make local models work well with OpenClaw. Being a maintainer of this specific vertical, I need to react quickly to any P0 issues.
For more details please read the original article at Hugging Face.
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