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Qwen3.6-35B-A3B: Agentic coding power, now open to all

qwen.ai

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Re: Qwen3.6-35B-A3B: Agentic coding power, now open to all

#341

Post by duzer65657 »

rafaelmn wrote: post #314
jubilanti wrote: post #302

Earlier quoted context omitted.

I wonder when pelican riding a bicycle will be useless as an evaluation task. The point was that it was something weird nobody had ever really thought about before, not in the benchmarks or even something a team would run internally. But now I'd bet internally this is one of the new Shirley Cards.

I mean look at the result where he asked about a unicycle - the model couldn't even keep the spokes inside the wheels - would be rudimentary if it "learned" what it means to draw a bicycle wheel and could transfer that to unicycle.

it's the frame that's surprisingly - and consistentnly - wrong. You'd think two triangles would be pretty easy to repro; once you get that the rest is easy. It's not like he's asking "draw a pelican on a four-bar linkage suspension mountainbike..."

Re: Qwen3.6-35B-A3B: Agentic coding power, now open to all

#343

Post by homebrewer »

kaliqt wrote: post #249
znnajdla wrote: post #196

Earlier quoted context omitted.

Some tasks don’t require SOTA models. For translating small texts I use Gemma 4 on my iPhone because it’s faster and better than Apple Translate or Google Translate and works offline. Also if you can break down certain tasks like JSON healing into small focused coding tasks then local models are useful

Is it really better? In which languages?

I've been using gemma4 for translating Mongolian to English. It runs circles around Google Translate for that language pair, it's not even close.

Re: Qwen3.6-35B-A3B: Agentic coding power, now open to all

#344

Post by spuz »

storus wrote: post #251
mudkipdev wrote: post #242

Earlier quoted context omitted.

Re-read that

You should. 3.5 MoE was worse than 3.5 dense, so expecting 3.6 MoE to be superior than 3.5 dense is questionable, one could argue that 3.6 dense (not yet released) to be superior than 3.5 dense.

Ok but you made a claim about the new model by stating a fact about the old model. It's easy to see how you appeared to be talking about different things. As for the claim, Qwen do indeed say that their new 3.6 MoE model is on a par with the old 3.5 dense model:

> Despite its efficiency, Qwen3.6-35B-A3B delivers outstanding agentic coding performance, surpassing its predecessor Qwen3.5-35B-A3B by a wide margin and rivaling much larger dense models such as Qwen3.5-27B.

https://qwen.ai/blog?id=qwen3.6-35b-a3b

Re: Qwen3.6-35B-A3B: Agentic coding power, now open to all

#345

Post by magicalhippo »

danielhanchen wrote: post #198
Aurornis wrote: post #176

Earlier quoted context omitted.

Unsloth is great for uploading quants quickly to experiment with, but everyone should know that they almost always revise their quants after testing. If you download the release day quants with a tool that doesn’t automatically check HF for new versions you should check back again in a week to look for updated versions. Some times the launch day quantizations have major problems which leads to early adopters dismissi…

We re-uploaded Gemma4 4 times - 3 times were due to 20 llama.cpp bug fixes, which we helped solve some as well. The 4th is an official Gemma chat template improvement from Google themselves, so these are out of our hands. All providers had to re-fix their uploads, so not just us. For MiniMax 2.7 - there were NaNs, but it wasn't just ours - all quant providers had it - we identified 38% of bartowski's had NaNs. Ours w…

Appreciate the work of your team very much.

Though chat templates seem like they need a better solution. So many issues, seems quite fragile.

Re: Qwen3.6-35B-A3B: Agentic coding power, now open to all

#346

Post by badsectoracula »

999900000999 wrote: post #219

Looking to move off ollama on Open Suse tumbleweed. Should I use brew to install llma.ccp or the zypper to install the tumbleweed package?

You can compile it from source, all you need to do is clone the repository and do a `cmake -B build -DGGML_VULKAN=1` (add other backends if you want) followed by a `cmake --build build --config Release` and then you get all the llama tools in the `build/bin` (including `llama-server` which provides a web-based interface). There is a `docs/build.md` that has more detailed info (especially if you need another backend, though at least on my RX 7900 XTX i see no difference in terms of performance between Vulkan and ROCm and the former is much more stable and compatible -- i tried ROCm for a bit thinking it'd be much faster but only ended up being much more annoying as some models would OOM on it while they worked on Vulkan -- if you or NVIDIA hardware all this may sound quaint though :-P).

Re: Qwen3.6-35B-A3B: Agentic coding power, now open to all

#348

Post by evilduck »

prirun wrote: post #313
simonw wrote: post #270

I've been running this on my laptop with the Unsloth 20.9GB GGUF in LM Studio: https://huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF/blob/mai... It drew a better pelican riding a bicycle than Opus 4.7 did! https://simonwillison.net/2026/Apr/16/qwen-beats-opus/

The flamingo on Qwen's unicycle is sitting on the tire, not the seat. That wins because of sunglasses?

Can a benchmark meant as a joke not use a fun interpretation of results? The Qwen result has far better style points. Fun sunglasses, a shadow, a better ground, a better sky, clouds, flowers, etc.

If we want to get nitty gritty about the details of a joke, a flamingo probably couldn't physically sit on a unicycle's seat and also reach the pedals anyways.

Re: Qwen3.6-35B-A3B: Agentic coding power, now open to all

#349

Post by i5heu »

Aurornis wrote: post #176
homebrewer wrote: post #18

Already quantized/converted into a sane format by Unsloth: https://huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF

Unsloth is great for uploading quants quickly to experiment with, but everyone should know that they almost always revise their quants after testing. If you download the release day quants with a tool that doesn’t automatically check HF for new versions you should check back again in a week to look for updated versions. Some times the launch day quantizations have major problems which leads to early adopters dismissi…

Thank you very much for this comment! I was not aware of that.

Re: Qwen3.6-35B-A3B: Agentic coding power, now open to all

#350

Post by evilduck »

danielhanchen wrote: post #243
evilduck wrote: post #232

Earlier quoted context omitted.

I just wanted to express gratitude to you guys, you do great work. However, it is a little annoying to have to redownload big models though and keeping up with the AI news and community sentiment is a full time job. I wish there was some mechanism somewhere (on your site or Huggingface or something) for displaying feedback or confidence in a model being "ready for general use" before kicking off 100+ GB model downloa…

Hey thanks - yes agreed - for now we do: 1. Split metadata into shard 0 for huge models so 10B is for chat template fixes - however sometimes fixes cause a recalculation of the imatrix, which means all quants have to be re-made 2. Add HF discussion posts on each model talking about what changed, and on our Reddit and Twitter 3. Hugging Face XET now has de-duplication downloading of shards, so generally redownloading…

Ah thanks, I wasn't aware of #3, that should be a huge boon.
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