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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

#231

Post by Gracana »

JKCalhoun wrote: post #217
WithinReason wrote: post #106

Earlier quoted context omitted.

It's on the page: Precision Quantization Tag File Size 1-bit UD-IQ1_M 10 GB 2-bit UD-IQ2_XXS 10.8 GB UD-Q2_K_XL 12.3 GB 3-bit UD-IQ3_XXS 13.2 GB UD-Q3_K_XL 16.8 GB 4-bit UD-IQ4_XS 17.7 GB UD-Q4_K_XL 22.4 GB 5-bit UD-Q5_K_XL 26.6 GB 16-bit BF16 69.4 GB

"16-bit BF16 69.4 GB" Is that (BF16) a 16-bit float?

https://en.wikipedia.org/wiki/Bfloat16_floating-point_format

Yes, however it’s a different format from standard fp16, it trades precision for greater dynamic range.

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

#232

Post by evilduck »

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…

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 downloads.

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

#233

Post by mtklein »

JKCalhoun wrote: post #217
WithinReason wrote: post #106

Earlier quoted context omitted.

It's on the page: Precision Quantization Tag File Size 1-bit UD-IQ1_M 10 GB 2-bit UD-IQ2_XXS 10.8 GB UD-Q2_K_XL 12.3 GB 3-bit UD-IQ3_XXS 13.2 GB UD-Q3_K_XL 16.8 GB 4-bit UD-IQ4_XS 17.7 GB UD-Q4_K_XL 22.4 GB 5-bit UD-Q5_K_XL 26.6 GB 16-bit BF16 69.4 GB

"16-bit BF16 69.4 GB" Is that (BF16) a 16-bit float?

Yes, it's a "Brain float", basically an ordinary 32-bit float with the low 16 mantissa bits cut off. Exact same range as fp32, lower precision, and not the same as the other fp16, which has less exponent and more mantissa.

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

#234

Post by nunodonato »

txtsd wrote: post #54
homebrewer wrote: post #18

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

So I can use this in claude code with `ollama run claude`?

https://sleepingrobots.com/dreams/stop-using-ollama/

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

#235

Post by storus »

adrian_b wrote: post #27
incomingpain wrote: post #2

Wowzers, we were worried Qwen was going to suffer having lost several high profile people on the team but that's a huge drop. It's better than 27b?

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).

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

#236

Post by zozbot234 »

Mikealcl wrote: post #223
arxell wrote: post #114

Earlier quoted context omitted.

Each has it's pros and cons. Dense models of equivalent total size obviously do run slower if all else is equal, however, the fact is that 35A3B is absolutely not 'a lot smarter'... in fact, if you set aside the slower inference rates, Qwen3.5 27B is arguably more intelligent and reliable. I use both regularly on a Strix Halo system... the Just see the comparison table here: https://huggingface.co/unsloth/Qwen3.6-35B…

Could you explain why prompt processing is the bottle neck please? I've seen this behavior but I don't understand why.

You should be able to save a lot on prefill by stashing KV-cache shared prefixes (since KV-cache for plain transformers is an append-only structure) to near-line bulk storage and fetching them in as needed. Not sure why local AI engines don't do this already since it's a natural extension of session save/restore and what's usually called prompt caching.

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

#237

Post by nunodonato »

arxell wrote: post #114
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!

Each has it's pros and cons. Dense models of equivalent total size obviously do run slower if all else is equal, however, the fact is that 35A3B is absolutely not 'a lot smarter'... in fact, if you set aside the slower inference rates, Qwen3.5 27B is arguably more intelligent and reliable. I use both regularly on a Strix Halo system... the Just see the comparison table here: https://huggingface.co/unsloth/Qwen3.6-35B…

I was hoping this would be the model to replace our Qwen3.5-27B, but the difference is marginally small. Too risky, I'll pass and wait for the release of a dense version.

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

#238

Post by [deleted] »

JKCalhoun wrote: post #217
WithinReason wrote: post #106

Earlier quoted context omitted.

It's on the page: Precision Quantization Tag File Size 1-bit UD-IQ1_M 10 GB 2-bit UD-IQ2_XXS 10.8 GB UD-Q2_K_XL 12.3 GB 3-bit UD-IQ3_XXS 13.2 GB UD-Q3_K_XL 16.8 GB 4-bit UD-IQ4_XS 17.7 GB UD-Q4_K_XL 22.4 GB 5-bit UD-Q5_K_XL 26.6 GB 16-bit BF16 69.4 GB

"16-bit BF16 69.4 GB" Is that (BF16) a 16-bit float?

[deleted]

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

#239

Post by huydotnet »

est wrote: post #229
WithinReason wrote: post #106

Earlier quoted context omitted.

It's on the page: Precision Quantization Tag File Size 1-bit UD-IQ1_M 10 GB 2-bit UD-IQ2_XXS 10.8 GB UD-Q2_K_XL 12.3 GB 3-bit UD-IQ3_XXS 13.2 GB UD-Q3_K_XL 16.8 GB 4-bit UD-IQ4_XS 17.7 GB UD-Q4_K_XL 22.4 GB 5-bit UD-Q5_K_XL 26.6 GB 16-bit BF16 69.4 GB

I really want to know what does M, K, XL XS mean in this context and how to choose. I searched all unsloth doc and there seems no explaination at all.

They are different quantization types, you can read more here https://huggingface.co/docs/hub/gguf#quantization-types

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

#240

Post by WithinReason »

JKCalhoun wrote: post #217
WithinReason wrote: post #106

Earlier quoted context omitted.

It's on the page: Precision Quantization Tag File Size 1-bit UD-IQ1_M 10 GB 2-bit UD-IQ2_XXS 10.8 GB UD-Q2_K_XL 12.3 GB 3-bit UD-IQ3_XXS 13.2 GB UD-Q3_K_XL 16.8 GB 4-bit UD-IQ4_XS 17.7 GB UD-Q4_K_XL 22.4 GB 5-bit UD-Q5_K_XL 26.6 GB 16-bit BF16 69.4 GB

"16-bit BF16 69.4 GB" Is that (BF16) a 16-bit float?

yes, it has 8 exponent bits like float32 instead of 6 like float16
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