Alibaba Qwen Releases Qwen3.8-Max: A 2.4 Trillion Parameter MoE Model and the Most Capable One in the Qwen Family to Date
Alibaba's Qwen team has officially moved Qwen3.8-Max out of preview and into general availability, bringing with it published per-token pricing and a commitment to release open weights in the coming week. The model is positioned as the most capable in the Qwen family, succeeding the earlier Qwen3 series that already spanned a range of sizes and architectures.
Qwen3.8-Max is built on a mixture-of-experts (MoE) architecture with 2.4 trillion total parameters. MoE designs activate only a subset of parameters for any given token, which allows very large theoretical parameter counts while keeping per-query compute more manageable than a dense model of equivalent size. The approach has become increasingly common among frontier labs looking to scale model capacity without proportional increases in inference cost.
On the input side, the model is multimodal - accepting text, images, and video alongside a 1 million-token context window. That context length places it in a bracket suited to long-document analysis, extended video understanding, and tasks that require holding large amounts of information in a single pass. Exact pricing tiers have been published alongside the general availability announcement, giving developers a clearer picture of what deployment costs will look like before the open weights arrive.
One notable gap at launch is the absence of a formal benchmark table. Independent and third-party evaluations will likely follow once the open weights are publicly released, at which point comparisons against other large MoE models - such as those from Mistral, DeepSeek, and Google - will be easier to make on standardized tasks. Until then, Alibaba's capability claims rest on internal assessments. The open-weight release next week will be a significant moment, as it will allow researchers to run their own evaluations and integrate the model into projects that require local or self-hosted deployment.
