Alibaba 推出 Qwen3.8-Max，计划于下周发布模型权重
Alibaba 表示，其拥有 2.4 万亿参数的模型计划于下周通过 Model Studio 发布，并计划发布模型权重，但许可条款尚未确定。
By Ryan Merket · Published
Primary source: CNBC
Why it matters
Eddie Wu is using Qwen releases to drive demand for Alibaba Cloud. Qwen3.8-Max matters if its performance produces recurring inference and agent usage beyond Alibaba's own products.
Alibaba, led by co-founder and 首席执行官 Eddie Wu, unveiled Qwen3.8-Max on Monday, August 3, saying the 2.4 trillion-parameter model is scheduled for release next week through Alibaba Cloud Model Studio. Alibaba also plans a 模型权重发布 next week, although the exact license and date remain unresolved. CNBC 报道 that Alibaba's Hong Kong shares rose 7% and its New York-listed shares gained roughly 4.5% in premarket trading.
The model announcement sits inside Wu's broader AI-cloud push at Alibaba. Wu has been Alibaba's CEO since September 2023, and Alibaba Cloud distributes the Qwen model family through Model Studio. Qwen3.8-Max gives Wu a new flagship for Alibaba's hosted services, with the release scheduled for next week.
Wu's history with Alibaba reaches back to its founding. He served as Alibaba's technology director in 1999, later becoming 首席技术官 of Alipay and Taobao. After helping build the technical systems beneath Jack Ma's commerce operation, Wu is using foundation models to recast Alibaba around AI and cloud computing.
The August 3 announcement made Alibaba's release plan more explicit and left the exact weight license and release date unresolved.
巨大模型但活跃核心较小
Alibaba 表示 Qwen3.8-Max contains 2.4 trillion total parameters, while its sparse mixture-of-experts architecture activates 95 billion parameters for a given workload. That distinction matters for developers evaluating inference costs and hardware requirements. The total count describes the capacity distributed across the model's experts; the active count is closer to the amount of computation used as the model processes each token.
Qwen3.8-Max accepts text, images and other visual inputs, with a context window of up to 1 million tokens. Alibaba is pitching it for coding, research, legal review, financial analysis, document processing and 3D design. Those workloads closely match the long-running agent tasks that frontier labs increasingly use to sell their highest-priced models.
Alibaba's visual claims are broad. Alibaba says Qwen3.8-Max can process hundred-page documents, full television series and 100-hour livestreams, then convert the material into searchable knowledge bases. Practical performance will hinge on accuracy across long inputs, tool reliability and the cost of processing that much material.
Wu needs the model to sell cloud usage
In Alibaba 五月对其三月季度业绩的说明, Alibaba said cloud revenue growth accelerated to 40% as its AI strategy delivered.
That is an Alibaba-reported figure, but it shows why Wu is shipping models at a rapid pace. Every Qwen release can create demand for inference, storage, agent tooling and Alibaba's chips. That gives Wu several ways to turn model adoption into revenue without depending on a standalone chatbot subscription.
Qwen3.8-Max fits that approach. Hosted access can generate usage revenue, while the planned 模型权重发布 could attract developers who want to inspect, customize or run the model elsewhere. The weight release should also clarify the license terms and the practical hardware burden facing teams that want to deploy a 2.4 trillion-parameter model themselves.
The Anthropic comparison needs independent testing
Alibaba says Qwen3.8-Max ranks fifth in Text Arena and second in Vision Arena, trailing only Anthropic 的 Claude Fable 5 on the vision ranking. Anthropic describes Fable 5 as a model for its hardest knowledge and coding work, including days-long tasks, deep research and document-heavy workflows in finance, law, analytics and architecture. Those use cases make it a target for Alibaba's enterprise cloud pitch.
The comparison should be treated as Alibaba's claim. The earlier Qwen3.8-Max preview arrived without a 模型卡 or independently reproduced benchmark results, TechTimes 在7月21日报道. Alibaba's Monday announcement includes leaderboard graphics, but developers will need outside evaluations across coding, tool use, long-context accuracy and multimodal tasks before treating the model as a consistent Fable substitute.
Parameter counts offer limited guidance in that comparison. Moonshot AI 的 Kimi K3 carries a larger stated total of 2.8 trillion parameters, while Qwen3.8-Max uses 2.4 trillion. Architecture, training data, reinforcement learning, inference settings and tool integration can matter as much as raw scale.
Wu's advantage comes from the distribution already surrounding Qwen. Alibaba owns the cloud infrastructure, model platform, chip operations and large consumer services where Qwen can be deployed. Monday's stock rally shows investors rewarded that structure for at least one session. Lasting gains will depend on whether outside developers reproduce Alibaba's performance claims and keep paying to run the model after the announcement attention fades.