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Chronicles

The story behind the story

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Alibaba launches a 2.4T parameter Qwen3.8 Max preview that it says rivals frontier AI models and is second only to Fable 5, plans to make it “open-weight soon”

Alibaba Group Holding Ltd. launched a preview version of its flagship Qwen3.8 Max model, which it described as comparable …

Bloomberg

Context & Ripple Effects

Alibaba’s Qwen line has moved between increasingly large proprietary previews and open-weight releases: the earlier Qwen3-Max-Preview exceeded 1T parameters, while the Qwen3 family established an open-weight reasoning-model track. The planned release posture for Qwen3.8 Max joins those two approaches.

The company also recently positioned Qwen3.5 as an open-weight multimodal model with lower claimed operating costs. A much larger flagship made available as open weight would make Alibaba’s performance claims more consequential for developers able to run or adapt the model.

First-order effects

  • Alibaba gains a new flagship preview to market against frontier systems, while the stated open-weight plan signals eventual access beyond a hosted API or closed product.
  • Developers and enterprises evaluating Qwen receive a potential high-end option, but its practical competitiveness remains contingent on the model’s eventual weights, licensing terms, and deployability.

Second-order effects

  • Rival model vendors face more pressure to distinguish closed offerings through reliability, tooling, distribution, or access terms rather than benchmark positioning alone.
  • A credible open-weight flagship can strengthen buyer leverage: customers can compare hosted frontier models against self-hosted or adapted alternatives, although the infrastructure burden of a 2.4T-parameter model may limit that option to well-resourced users.

Third-order effects

  • If frontier-scale models increasingly reach open-weight channels, competition may shift from exclusive model access toward efficient inference, cloud distribution, and enterprise integration.
  • The pattern could deepen the split between organizations that can operate very large models and those that consume them through providers, making compute availability and deployment economics central to model buyer power.

The trend: Alibaba’s release is one point in the push to pair frontier-model ambitions with open-weight distribution, shifting AI competition toward deployment economics and customer choice.

Discussion

  • @alibaba_qwen @alibaba_qwen on x
    Qwen3.8 is launching and going open-weight soon!🌐 With a massive 2.4T parameters, this model is continuously evolving. We believe it's one of the most powerful model available today, compatible to leading frontier AI models , second only to Fable 5. You don't have to wait to [ima…
  • @shuai_bai_ Shuai Bai on x
    Qwen3.8-Max Preview is now available for early access! This is our first trillion-parameter multimodal model. Based on my own experience, it not only delivers multimodal understanding that is competitive with—and in many cases ahead of—today's leading proprietary models, but
  • @emollick Ethan Mollick on x
    Regardless of what you think the answer should be, the inherent tension between a growing US regulatory/approval regime for frontier closed models & the lack of one for open models is going to need to be resolved in some way or another in the near future, with large consequences.
  • @natolambert Nathan Lambert on x
    Qwen's biggest models have never been open weight recently. Something is changing. You can imagine it like... Xi: no you're not allowed to keep your best model closed anymore, we weren't succeeding enough. A new era of competition for intelligence (if the benchmarks hold up).
  • @kimmonismus @kimmonismus on x
    Holy, Qwen 3.8 supposedly ahead of GPT-5.6 and only slightly behind Fable 5! - 2.4t Parameters - Open Source / Open Weight - full release soon, already available for testing as Qwen 3.8 max-Max-Preview What the frick, such insane release on a sunday?! The gap between US
  • @sudoingx @sudoingx on x
    Qwen 3.8 just got announced!. an open weight model, 2.4 trillion params, that alibaba's qwen team is calling second only to fable 5. if that holds, the number two model on earth, and the weights are coming to you, not a rented endpoint. every time this lab moves, it adds ten [ima…
  • @yzhang_cs Yu Zhang on x
    Open source is thriving! and now every open-weight model >2T adopts GDN/KDA in FLA 👀
  • @yacinemtb Kache on x
    1. Open source models are le bad and also decel 2. Government should make them banned 3. You should rent tokens from our price fixed oligopoly forever and be under threat of us removing access for any reason 4. My text is all lowercase because it's the vogue thing 5. No non ono […
  • @dannolan Dan Nolan on x
    It's pretty sick china's industrial policy is to just dump machine intelligence on the west
  • @scaling01 @scaling01 on x
    Qwen has a 2.4T model not surprising that some of their models are that large given that Qwen3.7-Max was the highest ranking chinese model on ECI
  • @suchenzang Susan Zhang on x
    how dare they give us the model for free after stealing from america! the audacity! the horror! such foolish decels! such blindness to agi! such short-sightedness to not withhold these dangerous capabilities from the evil plebs and nefarious state actors who will now run 2.4T [im…
  • @yuchenj_uw Yuchen Jin on x
    Open weights models really accelerated! > Qwen-3.8 (2.4T), “second only to Fable 5” > Kimi-K3 (2.8T), “only behind Claude Fable 5 Max and GPT-5.6 Sol Max” > GLM-5.2 (753B): remarkably efficient and capable. The demand we're seeing from Databricks customers is wild. This is
  • @perrymetzger Perry E. Metzger on x
    One of the horrible effects of Doomerism has been to reduce vital scientific communication, thus making US labs less competitive with time and giving an advantage to China (which is, paradoxically, far freer in this respect).
  • @guohao_li Guohao Li on x
    why can the china labs build glm-5.2, kimi k3, and many more to come? it is because of the openness. not just the open weights but the whole ecosystem. most of the work done in the china labs is carried by interns. i met brilliant undergrad and graduate interns who deeply