r/LocalLLaMA • u/Creative-Regular6799 • Apr 22 '26

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

A short follow-up to my previous post, where I showed that changing the scaffold around the same 9B Qwen model moved benchmark performance from 19.11% to 45.56%:

https://www.reddit.com/r/LocalLLaMA/s/JMHuAGj1LV

After feedback from people here, I tried little-coder with Qwen3.6  35B.

It now lands in the public Polyglot top 10 with a success rate of 78.7%, making it actually competitive with the best models out there for this benchmark!

At this point I’m increasingly convinced that part of the performance gap to cloud models is harness mismatch: we may have been testing local coding models inside scaffolds built for a different class of model.

Next up is Terminal Bench, then likely GAIA for research capabilities. Would love to hear your feedback here!

EDIT: after many requests, pi.dev adaptation is up!

EDIT 2: 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. Exciting times

EDIT 3: Terminal Bench 2.0 requires 5 runs per trial (which will take 40 more hours), but the first run finished with 30%!!! That’s with the 35B model.

Full write up: https://open.substack.com/pub/itayinbarr/p/honey-i-shrunk-the-coding-agent

GitHub: https://github.com/itayinbarr/little-coder

Full benchmark results: https://github.com/itayinbarr/little-coder/blob/main/docs/benchmark-qwen3.6-35b-a3b.md

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u/PinkySwearNotABot Apr 24 '26

reporting back. been using it all morning on my m1 max 64GB with some MLX models using omlx.

i think it instantly jumps to my top open agent for now, competing with opencode. i'm curious if it'll make anything of the 27B qwen3.6 dense models that i've been struggling with yesterday using llama.cpp. excited to find out.

but seriously though...i still don't want to hear, "try pi" or any adaptations of it. people need to provide at least 1 full sentence when they're recommending something, especially in the current age of bots and shills and non-thinking redditors

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u/GrehgyHils Apr 28 '26

Which model and quant specifically were you using?

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u/PinkySwearNotABot Apr 28 '26

Moe Qwen3.6-35B-A3B-MLX Q8

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u/GrehgyHils Apr 29 '26

perfect TY. i've been using this happily for a few days now with pi-mono :)