Does anyone know if they intend on releasing open source/weights variants for 3.8 or whether 3.6 was the last model they are/were doing that for?
Qwen 3.8
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Re: Qwen 3.8
#222[dead]
Re: Qwen 3.8
#223Earlier quoted context omitted.
Well, if you look at Alibaba's financials for FY 2026 https://data.alibabagroup.com/ecms-files/1514443390/5b9061ed... their sales and marketing expenses rose by about 100 billion RMB (10% of revenue), "primarily attributable to the investment in user experiences of Alibaba China E-commerce Group and user acquisition of Qwen app." So it seems like it's very important to them that people use the Qwen app and they're wi…
They’re also trying to take an axe to the lead the US has in the field at a time when sovereignty and “owning your platform” are the words of the day. Open source/open weight LLMs can steal the lunch of US competitors even if they aren’t the best of the best.
I think they're probably more concerned about their Chinese competition, considering that despite all that spending, the Qwen app still trails Bytedance's Doubao in terms of monthly active users: https://www.aicpb.com/ai-rankings/products/china-ai-rankings Though Quark in third place is also made by Alibaba, so put together they're almost caught up with Doubao + Jimeng (place 7, also ByteDance).
Re: Qwen 3.8
#224Earlier quoted context omitted.
Simpler (and faster): a single RTX Pro 6000 :)
Curious, do you find the 3.5 120B sized MoE works better than the dense 3.6 27B?
Yeah, Qwen3.5-122B-A10B-NVFP4 produces better responses than Qwen3.6-27B-NVFP4 (both from unsloth), but I'm mostly using them for programming in various ways, mostly Rust, Clojure, Python and JavaScript, and some translations tasks, but not much more than that, so YMMV.
Edit: as a concrete example, I'm working on a "optimization framework via agent harness" right now, Qwen3.6-27B-NVFP4 is often unable to actually complete the optimization within 100 turns, while Qwen3.5-122B-A10B-NVFP4 has no issues finishing within ~50 turns or so.
Re: Qwen 3.8
#225Does anyone know if they intend on releasing open source/weights variants for 3.8 or whether 3.6 was the last model they are/were doing that for?
will be releasing weights per their tweet announcing the model
https://xcancel.com/Alibaba_Qwen/status/2078759124914098291
Re: Qwen 3.8
#226Earlier quoted context omitted.
> What is needed the most right now is something similar to Bonsai 27B, with a modest memory footpint, but faster and more capable Yeah, that'd be neat, but that's not what this announcement is about at all: > With a massive 2.4T parameters
dont we all deem the ability to improve large models as the defacto capability to produce small ones?
I don't think so, they have different constraints and require different optimizations, being able to produce one of them doesn't mean you'll automagically be good at the other.
Re: Qwen 3.8
#227Does anyone know if they intend on releasing open source/weights variants for 3.8 or whether 3.6 was the last model they are/were doing that for?
[deleted]
Re: Qwen 3.8
#228Obligatory "Does it answer security questions?".
Re: Qwen 3.8
#229For those trying to get it to work in OpenCode with a Qwen Cloud Token Plan, this is what worked for me. Note that I've just matched Qwen 3.7 Max for the limits as I don't know exactly what they are.
"provider": {
"alibaba-token-plan": {
"models": {
"qwen3.8-max-preview": {
"limit": {
"context": 1048576,
"output": 65536
},
"modalities": {
"input": [
"text"
],
"output": [
"text"
]
},
"name": "Qwen3.8 Max Preview"
}
}
}
}Re: Qwen 3.8
#230So are locally-runnable models frozen at Qwen 3.6 now :/
Is qwen 3.6 27b the best model you can run locally at the moment? Not that I have the VRAM for it, but just curious.
I flip flop between qwen 3.6 27b and qwen 3.6 35b 4b active.
But there’s also the quantization of DeepSeek v4 flash called dwarfstar