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Qwen 3.8

原网页

https://www.qwencloud.com/pricing/token-plan

Comments URL: https://news.ycombinator.com/item?id=48966120

Points: 906

# Comments: 634

Hacker News 讨论

909 points · 634 comments · 查看原帖

  1. cnhwl

    I’m a developer from China. So, is this what Hacker News is all about? Whenever a model comes from China, the comments section stops discussing its technical architecture, optimisation points or real-world performance, and instead starts going on about politics, human rights and all that rubbish? To be honest, we Chinese IT professionals possess a genuine geek spirit. That’s why you’re lagging behind in open-source competitions—it’s got nothing to do with politics; you’ve simply lost sight of your original aspirations.

  2. simonw

    (I can't draw a pelican for this one because Alibaba Cloud have flagged my email address and won't let me pay them for access. So I'm waiting for the open weights release, or for the new model to show up on OpenRouter.)

  3. adrian_b

    I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July. Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8. I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to better compete with Moonshot AI. In any case, from this competition in LLMs, we win.

  4. vitorgrs

    Deepseek 4 "final" version is imminent as well. Will probably be at Opus 4.8 level, and I find it pretty big deal because of Deepseek price...

  5. 5701652400

    in my experience of 1 month daily use, Qwen 3.7 Pro is just unusable. wastes too much time, goes off track, useless stuck loops, cannot debug at all. Deepseek V4 Pro is night-and-day compare to Qwen. actually Qwen models seems the worst SWE experience so far. and it is super expensive compare to Deepseek. cannot delegate anything to it, cannot use it real-time low-level tasks either. totally unusable.

  6. SwellJoe

    Qwen is the most censored of the Chinese models in my testing, which makes me wonder in what other ways it is compromised. Open weights doesn't really reveal what's in there. And, in my tests, existing Qwen models are not at the pareto frontier of any metric; DeepSeek V4 Pro is better, faster, and much cheaper than Qwen 3.7 Max. (DeepSeek is also among the least censored of the Chinese models.) I guess we'll see if the "second only to Fable" hype pans out. In my limited experience with Kimi K3 (I signed up for a month of the $19 plan) it's slower and chews a lot more, so ends up being pretty expensive; one little feature burned through almost the entirety of my five hour limit. The $20 GPT plan is a lot more useful and includes 5.6 Sol, which is fast and token-efficient enough to be quite usable even with the small plan.

  7. overgard

    I've been using Qwen 3.6 27B with LMStudio, and I was pleasantly surprised with it, although it was a little slow. I found mtplx last night, and it really wasn't an exaggeration to say that it ran the model 2-3x faster which was super impressive. I'm trying to move to local models as much as I can, and I'm finding that it's becoming more and more practical. Admittedly this is on a $6000 dollar laptop (M5 Max Macbook with the specs maxxed out), so the hardware is still a bit out of reach for most people (the AI industry isn't exactly helping here..), but I'm getting the impression that the future is going to be smaller models with more focused training running locally. The danger of giving all your data to these cloud providers just seems too big to me, and I think they're going to start charging insane amounts when they need to show a profit.

  8. Schlagbohrer

    I have been using the docling software for PDF and XLSX reading/viewing/comprehension by my local qwen3.6. Claude was telling me that docling includes within it a very small LLM model just to assist with what is basically "super OCR". We are definitely in this era of ultra-mega-huge frontier models and super-tiny-micro models, all finding their uses. On an aside I tested docling by giving it the Ronin TTRPG rulebook PDF and it did an astounding job of converting it all into .txt and .md. Given the wild graphic design of the book that's pretty astounding. Next we'll see if it can read the other Borg books like Mörk Borg and Cy Borg, which are also famous for their messy information.