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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: 813

# Comments: 568

Hacker News 讨论

817 points · 569 comments · 查看原帖

  1. 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.

  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. nsbk

    Bring it on! Hoping that they release smaller sizes of Qwen3.8. I use the 35B MoE and 27B dense models locally and most of the time I don’t need to reach out to Claude. Extremely useful specially when requests include sensitive and/or personal data

  4. 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.

  5. 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...

  6. 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.

  7. mchusma

    I counted the other day and there were at least 12 different providers with "better than Opus 4.5 performance" on Artificial Analysis, Opus 4.5 being Anthropic's December release that many say kicked off the latest acceleration. Which is totally insane competition, particularly given how low switching costs. I personally think that Opus 4.5 level performance is sufficient for most apps and usecases, as they get deployed.

  8. beefsack

    For 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" } } } }