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Qwen3.8-Max: A New Bar for Coding and Cowork

qwen.ai

211–220 of 652 posts

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#211
post #205

They've also announced Qwen3.8-27B being released open-weight next week. Qwen3.6-27B is widely regarded as one of the best local models, especially since nothing else comes close to it, that isn't benchmaxxed, without being significantly larger. If 3.8 truly improves upon it that would be awesome.

Some advice I got from another HN Mac user was to run local models in energy saver mode. You'll get slightly reduced tokens, but the laptop won't overheat and the fans won't go wild.

Oh. I've been using an icepack under my laptop to keep mine cool. I'm watching it with llamatop to see if the GPU is actually active or not, aw activity monitor wasn't showing me what I wanted.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#212

Earlier quoted context omitted.

The US also isn't energy-limited. They'll just price out all humans living there from buying any electricity. EDIT: This was obviously meant to be facetious with the intent to highlight the negative effects on the general population that datacenter buildout has in the US.

USA vs. China energy production graph is wild https://stanfordreview.org/content/images/2025/10/us_china_p... States have had trouble delivering expected EV charging capacity btw Why aren’t we considered energy limited?

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Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#213
post #170

The visual web development / perceptionbench scores are very promising for image->html flows. Here are some test results. Original designs: https://image.non.io/257dc9cb-9e6b-4e00-8f12-23ea5e073649.we... These are fairly rich, pattern-heavy, nuanced designs. I've asked each to create it as a SPA where the map flows behind it. Opus 5 results: https://html.non.io/opusAcmeBooks Qwen 3.8 max results: https://html.non.io/…

So Opus introduced a container with overflow:scroll in the middle of the page, while Qwen didn't? That's interesting in terms of "smartness".

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#214
post #176

They've also announced Qwen3.8-27B being released open-weight next week. Qwen3.6-27B is widely regarded as one of the best local models, especially since nothing else comes close to it, that isn't benchmaxxed, without being significantly larger. If 3.8 truly improves upon it that would be awesome.

For those of us who don't have the time to follow closely, Qwen3.6-27B being Open Source and Open Weight, what level is this compared to other Western paid version? Just so that we know what 3.8 would be like. I currently have about 150 Tabs of Antirez posting on AI and running local model I haven't had the time to read. And there are probably some prerequisite reading or other research in between as well. I just wis…

> what level is this compared to other Western paid version?

IMHO this is a difficult question to answer. Part of the power of paid models comes from the software supporting it. With local models, you have tons of workflows that can severely influence the quality of the result.

In my personal experience, the SOTA models are way more consistent and can handle more complex questions. Part of that is (probably) because I don't let my local model access the internet, while paid models do use the internet to look at docs etc.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#215
post #66
post #20

Once OpenAI and Anthropic are public, every such announcement will become a reliable sell signal

Agree, I don't necessarily see a strong argument favoring OpenAI or Anthropic here. In the interest of perspective, can anyone (perhaps playing devil's advocate) give one? The open models are now good enough for what I want to do with them, let alone any future improvements. And factoring in efficiency gains, a model in the ~70b range starting to satisfy my needs would completely obviate the need to pay others for in…

> In the interest of perspective, can anyone (perhaps playing devil's advocate) give one?

I have numerous cases where Sol failed and only Fable could solve a problem. For example yesterday I was merging a Q2 curved with a Bezier curved face in 3D using OpenSCAD. I tried for over 2 hours with Sol 5.6 high and x-high.

Fable two-shotted it in about 30 minutes.

In my experience open models (or GLM, DS and Kimi) are radically worse than either of Claude or ChatGPT at these tasks.

I think there is a huge "long tail" of tasks like this where the frontier labs are ahead, and I think this long tail is quite important.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#216

Earlier quoted context omitted.

Qwen3.6-35B is my daily driver for AI, and what convinced me to cancel my Claude subscription back in April. The Qwen3.6 line is easily the best local model I've tried, and I've tried a lot. I've got it diligently grinding away on my laptop right now, reviewing and fixing some bugs in my F# code.

Qwen-3.6-35B-A3B was our "gateway drug" into switching our organisation to agent/harness-first coding. Particularly, I had one team member who was extremely sceptical of AIs/LLMs/harnesses and refused to use them. One day he said "Well, I have an RTX 5090 doing nothing... should I try to get something up on it?" and a few minutes later he had 3.6-35B loaded up, running OpenCode. It continues to be a workhorse to this…

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Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#217
post #67

I think the window for a ban of open weight models is closing fast so let's hope US administration is going to miss it and we get Fable-level models (at least in some aspects) with open weights without infringing any newly introduced law as a long-term local baseline.

They can't enforce a ban. Companies can just download the models and run them on MacBooks or GPUs (or the cloud) and USG has no idea. It would also hurt the administration's funding from corporate tech (companies don't like to fund politicians who restrict them). I'm not saying the administration won't do it, it would just be very dumb.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#218
post #210
post #170

The visual web development / perceptionbench scores are very promising for image->html flows. Here are some test results. Original designs: https://image.non.io/257dc9cb-9e6b-4e00-8f12-23ea5e073649.we... These are fairly rich, pattern-heavy, nuanced designs. I've asked each to create it as a SPA where the map flows behind it. Opus 5 results: https://html.non.io/opusAcmeBooks Qwen 3.8 max results: https://html.non.io/…

Update: Tried using Qwen Desktop. It told me it succeeded, and linked me to the folder it created it in. That folder didn't exist, I asked Qwen where the files were, and it attempted to create them again. Stopped it, and asked what happened to the original files. Qwen Desktop apparently doesn't have access to the local file system, but continued merrily along without warning about that. https://image.non.io/07a153cd-…

Also tried Qwen Code. Tried it with a coding plan and it 401'd. Tried it with an api key I loaded up with pay-as-you-go credits and it 401'd.

It did a self update and it worked for a single request (me just saying hi). Pasted in the prompt to build the page and it 401'd.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#219

At $2/$6, it can be much more "approachable" than K3. Wondering what have they done differently to be able to afford this price (that K3 couldn't, apparently - most other providers offer similar prices to K3 itself).

Qwen is Alibaba. Alibaba rents hardware to Moonshot. So Qwen always has the option of cheaper hardware. Qwen might also break even on inference as competitive advantage since Alibaba has wider pockets. Alibaba also owns a 36% stake in Moonshot, which must make pricing discussions interesting... but then again Google rents hardware to OpenAI and Anthropic.

Re: Qwen3.8-Max: A New Bar for Coding and Cowork

#220

Earlier quoted context omitted.

I have been using Qwen3.6-35B-A3B as my daily driver as well and its been phenomenal when it comes to coding

How do you use a 72GB model as your daily driver locally?

Apple Silicon. But: there's no need to use the FP16 version. At 8-bit precision the quality loss is almost imperceptible. That cuts the footprint to 36GB. Which is great for a 64GB Mac, because you have room for plenty of context. 6-bit also works nicely at 26GB + context.

You want to use the newer quantization formats like Unsloth's UD quants or oQe, where the weights are selectively quantized using a calibration dataset so that important weights are left at/closer to full precision.

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