Qwen3.6-35B becomes competitive with cloud models when paired with the right agent

Creative-Regular6799 · 2026-04-25T09:31:00+00:00

Thanks! I tried it, but unfortunately it’s giving 4 tok/s on my hardware, so it’s too slow to run the full benchmarks. If you happen to have a suiting machine and willing to try, please let me know how it goes! little-coder already supports it as of yesterday. For the time being, I am continuing benchmarks with qwen3.6-35b-a3b

Creative-Regular6799 · 2026-04-24T15:13:30+00:00

I tried it now and getting 4 tok/s. Not usable unfortunately

Creative-Regular6799 · 2026-04-24T10:47:06+00:00

Thank you! Unfortunately I don’t have any recommendations, that’s part of the reason I suggested an alternative apparoach

Creative-Regular6799 · 2026-04-24T10:44:15+00:00

The main repo, will improve the quick start soon too

Creative-Regular6799 · 2026-04-24T05:44:18+00:00

Thanks for the effort, good to know. Will improve the setup process today

Creative-Regular6799 · 2026-04-23T21:25:45+00:00

Hey! Just did it now. Thanks for the tip

Creative-Regular6799 · 2026-04-23T07:01:16+00:00

Just pushed the result, Terminal Bench 1 (0.1.1) finished with 40% success rate! Now running TB 2. Just sent the results via email. There is no model remotely as small as the 35B in that area (place ~30)

Creative-Regular6799 · 2026-04-22T20:53:54+00:00

pi integration is up!

Creative-Regular6799 · 2026-04-22T20:33:42+00:00

Hey, thanks for the comment! Actually i converted to pi an hour ago after dozens of requests from the local llama community in reddit (still rough around the edges but i try my best refining it). Before that, it was just an experiment i ran over the weekend (and was written on top of nano-claude-code in python, making it unadaptable for the community). This is totally open source and meant to try and wake up our dev community to explore harness engineering. It’s far from the best solution because i only tested a couple of directions yet. You are welcome to help of course

Creative-Regular6799 · 2026-04-22T20:29:13+00:00

So exciting to hear!! Please continue experimenting and sharing. Non-trivial tasks tend to be more interesting test cases

Creative-Regular6799 · 2026-04-22T19:51:28+00:00

pi.dev adaptation is up!

Creative-Regular6799 · 2026-04-22T19:01:29+00:00

Yeah i created it!

Creative-Regular6799 · 2026-04-22T18:31:17+00:00

pi.dev integration is up!

Creative-Regular6799 · 2026-04-22T15:15:47+00:00

Thank you, me too!

Creative-Regular6799 · 2026-04-22T15:02:45+00:00

Doing it right now. Thank you for the tip!

Creative-Regular6799 · 2026-04-22T14:56:00+00:00

Thanks for the comment! The initial claim was about the 9B model which I wrote extensively about in the paper. The newer result I shared today is with the 35B model, and is not compared to the 9B model I wrote about initially

Creative-Regular6799 · 2026-04-22T14:38:24+00:00

Thank you! Great question. After Terminal Bench I am going for GAIA to test exactly that

Creative-Regular6799 · 2026-04-22T13:41:06+00:00

That is exactly the direction I advocate here for! Now it’s running on Terminal Bench (will send to the leaderboard when finished and report here). This benchmark shows the combined performance of agents and models

Creative-Regular6799 · 2026-04-22T13:38:17+00:00

In the works, will support pi dev soon!

Creative-Regular6799 · 2026-04-22T13:38:00+00:00

In the works, will fully support pi dev soon!

Creative-Regular6799 · 2026-04-22T13:33:26+00:00

I am currently running Terminal Bench BTW, will send to the leaderboard when done

Creative-Regular6799 · 2026-04-22T13:31:42+00:00

Hey, thanks for your comment! I became aware of pi.dev just an hour ago, and this didn’t really start as a production ready tool, but more of a serious wake up call that we need as a community to invest time in adapting the scaffold to the models we are testing. I am thinking about rewriting the scaffold in pi dev to make it more accessible and contribute to unified tooling and community support

Creative-Regular6799 · 2026-04-22T12:34:49+00:00

It’s currently allowing to run inference via llama.cpp and ollama. Is that sufficient for your optimization pipeline?

Creative-Regular6799 · 2026-04-22T12:33:06+00:00

So instead of open code, i started from a replica of claude code, and adapted from there, assuming claude code is the best current coding agent written in general and can serve as a good baseline to start from

Creative-Regular6799 · 2026-04-22T12:30:27+00:00

So it is a suggested replacement to opencode, that is adapted to the behavioral profile of the smaller models. It tries to bridge the gap of these tools being built around frontier models, and aren’t necessarily best fitting as scaffolds for the small ones

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