Qwen3.8

• 1. overview (804 chars)

  Qwen3.8 is the new generation flagship model of Alibaba's Tongyi Qianwen series. It was officially announced during the World Artificial Intelligence Conference (WAIC) in Shanghai on July 19, 2026. The total parameter scale reaches 2.4 trillion (2.4T). It is Alibaba's first native multi-modal model to cross the trillion parameter threshold. The official claims that it "may be the most powerful model except Fable 5". The preview version Qwen3.8-Max-Preview has been launched on Alibaba Token Plan, Qoder and QoderWork, and it is promised that the official version will open source the weights. Third-party actual testing shows that it has indeed entered the first echelon in terms of coding and agent tasks, but its creative programming and motion aesthetics are still obvious shortcomings, and the official has not released any benchmark data so far. The statement "second in the world" can only be regarded as a marketing slogan for the time being.

• 2. Product background (1304 chars)

  Qwen3.8 comes from Alibaba Tongyi Qianwen (Qwen) team and is the largest base model of the Qwen family to date. Reviewing the evolution of the product line: Qwen3-Max with 1T parameters was released in September 2025, Qwen3.5 with 397B was open sourced in February 2026, and closed-source Qwen3.7-Max was launched in May 2026. Now Qwen3.8 directly increases the parameters to 2.4T, more than doubling the scale of the previous generation.   The timing of this release is intriguing. On July 11, Dark Side of the Moon just released the 2.8T parameter Kimi K3 and promised to make it open source. Three days later, Alibaba showed off Qwen3.8 on the WAIC stage. In the same week, DeepSeek V4 also appeared one after another. China's large model manufacturers have fully approached or exceeded the 2 trillion level in terms of parameter scale. Goldman Sachs' report in mid-July officially recommended the Chinese open source model for the first time, saying that it provides 80% to 90% of cutting-edge capabilities at a cost of about one-seventieth of GPT-5.6 Sol. The market reaction was also very direct: Alibaba’s share price rose 5.4% the day after the official announcement.   It is worth noting that Qwen3.8 has changed Alibaba’s previous route of “the flagship Max model only uses closed source API”. Qwen3.7-Max has not yet opened its weights, and Qwen3.8 has officially stated that it will be "open source soon." Although no specific date and license terms are given, if it is fulfilled, it will become one of the largest open source weight models in the world.

• 3. Product functions and usage experience (2339 chars)

  Qwen3.8 adopts a sparse mixed expert (MoE) architecture, and each token only activates a small part of the 2.4T total parameters (the amount of activation parameters is not officially disclosed). It is Alibaba's first trillion-level native multi-modal model. It supports the understanding and reasoning of text, images, videos, and documents. It has thinking modes, function calls, and built-in tool capabilities. The context window community generally uses 1M token configurations. The official focus of its core capabilities is on the two directions of coding engineering (Coding) and professional office (Cowork), supporting the Harness tool set, including Internet search, text search, image search, web crawling, code interpreter, etc., which can be called through compatible AI programming tools such as Cursor and Qwen Code.   The conclusions of the third-party actual test are relatively consistent: the basic coding skills are solid. Algorithm questions such as LRU Cache are passed in one go; a complete Todo application with React + TypeScript front-end and Flask back-end, 14 files are generated at one time, and the front-end and back-end are directly run through; given it a real GitHub warehouse, it can correctly analyze the structure, find 3 real bugs and complete the repairs, and the multi-step Agent execution process does not break the link. A blogger used a prompt word to let it generate a 3D interactive scene of "One hundred thousand heavenly soldiers besieging Huaguo Mountain". It used InstancedMesh to instantiate 12,000 heavenly soldiers at one time, and reduced the number of draw calls in a single frame from thousands to one. The engineering judgment is remarkable. In a comparative test in which three models jointly reconstructed the "Shit Mountain" website, Qwen3.8-Max ranked first with fast execution and high completion, surpassing Kimi K3 and GLM-5.2.   But the shortcomings are equally obvious. On the comparison question of 3D floating island creative portfolio, Qwen3.8 is the worst finished product among the six tested models: static scenes can be rendered, but almost all dynamic effect requirements such as scroll drive camera, object interaction, and Bloom post-processing are missing. Let it draw the SVG of "Pelican Riding a Bicycle", and the thinking mode idled for more than four minutes without outputting a result. Many users have reported that it is seriously "biased": Three.js scenarios can be solved in one conversation, but Python regular expressions are not correct even in three versions. The unexpected highlight is the Chinese long article writing. The paragraph structure and argument level are significantly better than GPT-5.6's performance on the same topic, and there is no typical AI cliche flavor.

• 4. Pricing and business model (1222 chars)

  In the preview stage, Qwen3.8-Max-Preview does not provide standard APIs billed by token, and is only open to Token Plan subscribers (personal and team editions) and Qoder and QoderWork users. The limited-time discount is very strong: the billing factor during the day is reduced from 0.5x to 0.05x (equivalent to 10% off), and the personal version is as low as 0.2% off from 22:00 to 08:00 at night. The personal version of Token Plan starts at 35 to 39 yuan per month, and the enterprise version is priced at 150 yuan per month. It only supports the North China 2 (Beijing) region. The preview endpoint is compatible with both OpenAI and Anthropic API formats. You can access tools such as Claude Code, Cursor, and OpenCode by changing the configuration. Ordinary users can also directly select preview models on Qianwen PC and Web (chat.qwen.ai) without logging in.   In terms of business model, Alibaba continues the dual-track approach of "open source traffic and cloud service monetization": first use a subscription-based preview period to collect real user feedback to complete the final polish, then open source the weight to expand ecological influence, and undertake commercialization of cloud inference services. Some overseas users reminded that the contracting party of the international version of Token Plan is Intelligent Cloud Computing Company in Singapore. It is worth paying attention to the contracting party before making payment.

• 5. User reviews (1339 chars)

  Positive reviews focused on coding and office scenes. Some front-end developers said that it can create interactive Three.js 3D components from scratch in just one conversation. "This is the most outrageous front-end capability I have ever seen. Even Kimi K3 cannot do this." The collaborative working scenarios within the DingTalk ecosystem—meeting minutes, automatic weekly reports, and Excel organization—have been rated as “amazing” by users. RPG web games and complete games with branching endings are generated with one prompt word, and the degree of completion far exceeds expectations. The nearly free preview pricing is also generally considered to be extremely cost-effective. One user actually measured that four large coding tasks only consumed 6% of the weekly quota.   There are three main categories of negative feedback. The first is the lack of reliability. In a blind test, overseas blogger LlamaBrew found that the multi-threaded crawler it wrote "has the clearest framework and annotations like a textbook, but it runs with segfaults." He commented that it "looks like a freshly graduated academic, with perfect scores in theory but no real skills in practice." This comment once appeared on the homepage of Hacker News. Second, the thinking mode is slow and cannot be turned off in the free interface. Tests by Geeky Gadgets also pointed out that the output speed and efficiency are limited. Third, the rollover rate of creative and aesthetic tasks is high, and the comprehensive judgment ability of motion effects, interaction, and vision has obviously not kept up.

• 6. Industry evaluation (932 chars)

  The focus of industry media is highly consistent: the gap between propaganda and evidence. When Qwen 3.8 was released, there were no benchmark scores, no model cards, no technical reports, and no activation parameters. "Second only to Fable 5" was entirely derived from Alibaba's internal evaluation. This is in sharp contrast to Qwen3.7-Max’s practice of announcing model cards and SWE-bench Pro scores of 60.6 on the day it was released. The only third-party data currently comes from Trilogy AI's StackPerf blind test: under the same 269-file code base analysis task, Kimi K3 scored 83 points and Qwen3.8-Max scored 80 points. Although the single test cannot be conclusive, it does not support the claim of "second in the world".   The Verge and Business Insider called Qwen3.8-Max and Kimi K3 the “Chinese AI combo.” The consensus among domestic evaluations is that in pure coding scenarios it is in the same echelon as Kimi K3, with a gap of about ten percentage points from Fable 5; it may even be the best choice at this price for agent tasks; but under the comprehensive evaluation caliber, it is ranked second.

• 7. Controversies and Risks (823 chars)

  The biggest controversy is "streaking release": claiming to be second but unable to produce any verifiable data. Someone on Hacker News bluntly said that Qwen has an old reputation as a "benchmark expert" and "trust us, it's #2" is exactly the problem that the benchmark form should solve. At the risk level, the preview infrastructure will be officially removed or replaced and is not suitable for production environments; the open source commitment does not have a date, license, or checkpoint name, and you need to wait and see before it is fulfilled; even after quantification, the 2.4T volume is far beyond the limit of a personal workstation. The r/LocalLLaMA community is more concerned about "it can't run even if it is open source." In addition, the model is obviously in an unfinished state of post-training. Iterating in "days" means that the capabilities and behavior may change at any time during the preview period, and the results before and after are not reproducible.

• 8. Applicable groups and usage suggestions (703 chars)

  If your workflow focuses on coding, full-stack development, warehouse-level bug fixing, data analysis, and Office automation, the current 10% off preview price is extremely cost-effective, and it is worth trying out Cursor or Claude Code immediately. Long-form Chinese writing is a hidden bonus. But if you need complex tasks such as "coding plus aesthetics" such as creative programming, 3D visualization, and front-end animation, it is still far from enough at this stage. It is recommended to continue to use Fable 5 or GPT-5.6. For users in the open source community, the rational approach is to wait until the weights are truly released and independent evaluations catch up before drawing conclusions. Ordinary users who want to try it out for free can directly go to chat.qwen.ai and select a preview model without registration.

• 9. Summarize (418 chars)

  Qwen3.8 is a release with "real strength and advanced publicity": the coding and agent capabilities have indeed reached the first echelon, but "second only to Fable 5" is just a marketing phrase before the public benchmark is presented. If the official version in one month can make up for the non-coding shortcomings and be open sourced as promised, it has the opportunity to become the world's strongest open source model; now, it is a large-scale public beta that uses users as a polishing process.

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  5a7l0v

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  看了那个三模型接管屎山代码的测试，Qwen3.8执行最快完成度最高，排在K3和GLM前面。不过它为了实现轮播直接把原有的拖动功能删了，还用复制大量内容的方式伪装无限循环，这种「快」是有代价的，大项目里这么干迟早埋雷。

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  RogerLee007

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  在Qoder里用了几天，官方给它的定位是深度推理办公首选，上下文能拉到1M。深度思考经常29秒就出结果，速度真不慢。

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  DAkra

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  预览版基础设施官方说了随时会移除替换，别拿去上生产。

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  掠影_2

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  国际版Token Plan的签约主体是新加坡一家叫Intelligent Cloud Computing的公司，不是alibabacloud的域名，付款前建议看清楚合同主体。

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  RGray_2021

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  让它修我那个markdown编辑器的网页转md功能，之前用glm-5.2修了很久都搞不定，Qwen3.8蹬了21分钟真给修好了，公众号知乎百家号都能抓了。这种在真实工程里救火的能力比什么前端炫技都有说服力。

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  GKelly_2021

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  一句提示词让它做「十万天兵围攻花果山」3D场景，生成1400行代码，用InstancedMesh一次性实例化12000个天兵，单帧draw call从上千次压到1次。这十万天兵不是堆出来的，是算出来的，工程判断力是真有。

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  珊瑚_3

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  给它一个游戏剧本，直接产出带双感情线三种结局的完整RPG网页游戏，我连玩三遍才通关。就是代码1600行全挤一个文件里，IIFE老写法谈不上优雅。

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  GHallIII

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  复刻lusion.co翻车了，WebGL流体交互完全没啃下来，还原度也就50多分。但Hero区动画、GSAP平滑滚动这些还原接近90%，重要的东西倒是对了。

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  Web3DevEdwards

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  3D浮岛作品集那道题翻得很彻底，静态场景能渲染，但滚动驱动相机、物件交互、Bloom后处理全缺失，是测过的6个模型里成品最差的。创意编程这块它现在真不行，不是参数不够，是后训练还没做完。

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  郭芳

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  实测四次大型编码任务只消耗了周配额的6%，18美元档随便造。

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  heavyfish626

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  意外的是中文长文写作，让它写大模型发布潮的分析文章，段落结构和论证层次都有模有样，引用数据抽查是真的，没有那种「值得注意的是」的AI套话味，比GPT同题强不少。

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  Debra993

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  白天1折夜间0.2折，这定价基本等于白送，不试白不试。

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  Ja_cob882

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  免登录就能在chat.qwen.ai选预览版，白嫖党狂喜。

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  DAlop

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  X上快600万浏览，但讨论都集中在「能聊不等于能用，承诺不等于交付」，大家等的是benchmark表、激活参数量和HF上带许可证的真实权重。

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  silverkoala134

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  用它复刻了宝可梦红宝石，小镇草丛实验室三只初始怪都有，草丛随机遇敌，战斗有属性克制和经验反馈。它还自己写Playwright测试10/10通过，从下命令到修完bug大概2小时完工，这种开发效率之前哪敢想。

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  ABaileyK

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  让它把游戏改中文版，它会自己去找合适的开源字体，遇到实现阻碍自己完成方案设计，long-horizon agent和一次性代码生成的区别就在这。

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  邓鹏琪

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  思考模式是真的慢，让它画个鹈鹕骑自行车的SVG，四分多钟还在「调整鹈鹕比例」，最后我都懒得等了。免费界面还关不掉thinking，急用的时候挺折磨。

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  梁琳兰

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  钉钉生态里的办公场景是真惊艳，会议纪要周报Excel整理一条龙，这块比编程还稳。

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  AudeMathieu

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  海外博主盲测让它写多线程爬虫，代码框架最清晰注释像教科书，结果跑起来段错误。像刚毕业的学霸，理论满分实战缺根筋，这个比喻太精准了。

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  Catherine.EvansZ62

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  唯一的第三方盲测StackPerf里，K3拿83分它拿80，虽然就一道题说明不了什么，但至少不支持全球第二的说法。好在它44次工具调用一次都没失败，稳定性倒是加分。

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  whiteostrich642

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  r/LocalLLaMA那边没人关心排名，都在算2.4T的部署账，4bit量化光权重就要1.2TB，一张H200才141G显存，开了源普通人也跑不动，就盼着出个蒸馏小杯。

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  ROric

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  LRU Cache一次过，React加Flask的完整Todo应用14个文件一次性生成直接跑通。给它真实GitHub仓库让它找bug，提的3个问题逐个验证都真实存在，克隆到本地修完还能跑，Agent多步执行全程没断链。就冲编码这块，仅次于Fable 5的说法没有想象中那么水。

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  ABaker_Plus366

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  有点偏科，Three.js的3D交互组件一轮对话搞定，但让它写个Python正则，给了三个版本都不对，笑死。

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  天涯_18

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  Kimi K3刚发三天阿里就在WAIC亮Qwen3.8，同一周DeepSeek V4也出来了，国产模型这波内卷看得过瘾。

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  竹影216

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  2.4T参数还承诺开源，要是真放权重出来就是最大的开源模型之一了。不过发布当天没有benchmark没有模型卡没有技术报告，连激活参数量都不说，「仅次于Fable 5」全靠自封，HN上都在说Qwen有benchmark专家的旧名声，这次连表都不给了。

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  徐磊霖

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  预览端点兼容OpenAI和Anthropic两种API格式，改个配置就能接进Claude Code和Cursor，这点对开发者太友好了。

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