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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

#361

Post by rubiquity »

storus wrote: post #235
adrian_b wrote: post #27

Earlier quoted context omitted.

Their previous model Qwen3.5 was available in many sizes, from very small sizes intended for smartphones, to medium sizes like 27B and big sizes like 122B and 397B. This model is the first that is provided with open weights from their newer family of models Qwen3.6. Judging from its medium size, Qwen/Qwen3.6-35B-A3B is intended as a superior replacement of Qwen/Qwen3.5-27B. It remains to be seen whether they will als…

> Qwen/Qwen3.6-35B-A3B is intended as a superior replacement of Qwen/Qwen3.5-27B Not at all, Qwen3.5-27B was much better than Qwen3.5-35B-A3B (dense vs MoE).

Not sure why you're being downvoted, I guess it's because how your reply is worded. Anyway, Qwen3.7 35B-A3B should have intelligence on par with a 10.25B parameter model so yes Qwen3.5 27B is going to outperform it still in terms of quality of output, especially for long horizon tasks.

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

#362

Post by vlapec »

wrxd wrote: post #210
fooblaster wrote: post #5

Honestly, this is the AI software I actually look forward to seeing. No hype about it being too dangerous to release. No IPO pumping hype. No subscription fees. I am so pumped to try this!

Same here. I really hope in a near future local model will be good enough and hardware fast enough to run them to become viable for most use cases

No need to hope; it is inevitable.

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

#363

Post by akavel »

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?

Well, maybe the flamingo is a really good unicyclist...

https://youtu.be/Rrpgd5oIKwI

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

#364

Post by rubiquity »

mncharity wrote: post #347
tmaly wrote: post #275

What is the min VRAM this can run on given it is MOE?

Fwiw, with its predecessor's Qwen3.5-35B-A3B-Q6_K.gguf, on a laptop's 6 GB VRAM and 32 GB RAM, with default llama.cpp settings, I get 20 t/s generation.

Have you tried running llama.cpp with Unified Memory Access[1] so your iGPU can seamlessly grab some of the RAM? The environment variable is prefixed with CUDA but this is not CUDA specific. It made a pretty significant difference (> 40% tg/s) on my Ryzen 7840U laptop.

1 - https://github.com/ggml-org/llama.cpp/blob/master/docs/build...

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

#365

Post by blazzy »

lagniappe wrote: post #50
shevy-java wrote: post #14

I don't want "Agentic Power". I want to reduce AI to zero. Granted, this is an impossible to win fight, but I feel like Don Quichotte here. Rather than windmill-dragons, it is some skynet 6.0 blob.

Then who is Rocinante?

A dimming IBM x40 Thinkpad missing its F key.

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

#366

Post by zozbot234 »

rubiquity wrote: post #364
mncharity wrote: post #347

Earlier quoted context omitted.

Fwiw, with its predecessor's Qwen3.5-35B-A3B-Q6_K.gguf, on a laptop's 6 GB VRAM and 32 GB RAM, with default llama.cpp settings, I get 20 t/s generation.

Have you tried running llama.cpp with Unified Memory Access[1] so your iGPU can seamlessly grab some of the RAM? The environment variable is prefixed with CUDA but this is not CUDA specific. It made a pretty significant difference (> 40% tg/s) on my Ryzen 7840U laptop. 1 - https://github.com/ggml-org/llama.cpp/blob/master/docs/build...

Your link seems to be describing a runtime environment variable, it doesn't need a separate build from source. I'm not sure though (1) why this info is in build.md which should be specific to the building process, rather than some separate documentation; and (2) if this really isn't CUDA-specific, why the canonical GGML variable name isn't GGML_ENABLE_UNIFIED_MEMORY , with the _CUDA_ variant treated as a legacy alias. AIUI, both of these should be addressed with pull requests for llama.cpp and/or the ggml library itself.

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

#367

Post by stratos123 »

Miraste wrote: post #110
zozbot234 wrote: post #62

Earlier quoted context omitted.

The 27B model is dense. Releasing a dense model first would be terrible marketing, whereas 35A3B is a lot smarter and more quick-witted by comparison!

What? 35B-A3B is not nearly as smart as 27B.

One interesting thing about Qwen3 is that looking at the benchmarks, the 35B-A3B models seem to be only a bit worse than the dense 27B ones. This is very different from Gemma 4, where the 26B-A4B model is much worse on several benchmarks (e.g. Codeforces, HLE) than 31B.

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

#368

Post by [deleted] »

sowbug wrote: post #212
danielhanchen wrote: post #209

Earlier quoted context omitted.

Yep we can do that probs add a table - in general be post in discussions of model pages - for eg https://huggingface.co/unsloth/MiniMax-M2.7-GGUF/discussions... HF also provides SHA256 for eg https://huggingface.co/unsloth/MiniMax-M2.7-GGUF/blob/main/U... is 92986e39a0c0b5f12c2c9b6a811dad59e3317caaf1b7ad5c7f0d7d12abc4a6e8 But agreed it's probs better to place them in a table

Thanks! I know about HF's chunk checksums, but HF doesn't publish (or possibly even know) the merged checksums.

[deleted]

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

#369

Post by rexreed »

999900000999 wrote: post #286
rexreed wrote: post #261

Earlier quoted context omitted.

Why are you looking to move off Ollama? Just curious because I'm using Ollama and the cloud models (Kimi 2.5 and Minimax 2.7) which I'm having lots of good success with.

Ollama co mingles online and local models which defeats the purpose for me

You can disable all cloud models in your Ollama settings if you just want all local. For cloud you don't have to use the cloud models unless you explicitly request.

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

#370

Post by hparadiz »

bdangubic wrote: post #359
hparadiz wrote: post #352

Earlier quoted context omitted.

There are way too many good uses of these models for local that I fully expect a standard workstation 10 years from now to start at 128GB of RAM and have at least a workstation inference device.

or if you believe a lot of HN crowd we are in AI bubble and in 10 years inference will be dirt cheap when all of this crashes and we have all this hardware in data centers and it won't make any sense to run monster workstations at home (I work 128GB M4 but not run inference, just too many electron apps running at the same time...) :)

Inference will be dirt cheap for things like coding but you'll want much more compute for architectural planning, personal assistants with persistent real time "thinking / memory", as well as real time multimedia. I could put 10 M4s to work right now and it won't be enough for what I've been cooking.
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