Alibaba debuts Qwen3-Max-Preview, its largest AI model with over 1T parameters, showcasing strong benchmark performance; the model is not open source
Chinese e-commerce giant Alibaba's “Qwen Team” of AI researchers has done it again. After a busy summer in which the AI lab released …
VentureBeatCarl Franzen
Context & Ripple Effects
Alibaba’s cloud unit had already used Qwen releases to make comparative performance claims, including Qwen 2.5-Max’s claimed edge over named rivals. This release raises the stakes by placing the company’s largest model in a proprietary offering rather than an openly available one.
The Qwen roadmap later spans both an open-weight multimodal Qwen3.5 model and additional proprietary releases, making this launch an early signal that Alibaba was building separate access models for different parts of its AI portfolio.
First-order effects
Alibaba gains a new flagship model for customers seeking its highest-capability Qwen offering, with benchmark results serving as its immediate positioning tool.
Because the model is not open source, developers and enterprises must access it on Alibaba’s terms rather than independently inspect, modify, or self-host its weights.
Second-order effects
Rival model providers face added pressure to compete not only on benchmark claims but also on the access, deployment, and commercial terms attached to their frontier-tier models.
The closed release gives Alibaba a reason to channel demand through its own cloud and model-serving stack, while customers must weigh that convenience against reduced control over the model.
Third-order effects
If Alibaba continues pairing proprietary flagships with open-weight Qwen variants, the market could settle into a two-track model strategy: open releases for ecosystem adoption and closed models for premium capability and service capture.
That split would make buyer power increasingly depend on switching costs, deployment flexibility, and provider distribution—not parameter counts or benchmark rankings alone.
The trend: This is part of AI industrialization in which model vendors use a mix of open and closed releases to expand adoption while retaining control of their most commercially important capabilities.
.@benparr and I were one of the first investors into @DanielEdrisian / @alexcodes_ai. I loved what he was doing and we started chatting before he even joined YC. Excited to see what he builds at @OpenAI and waiting patiently to be the first check in his next company ❤️
🚀 Qwen-Max has successfully scaled to 1T parameters, and we're still pushing further. Hopefully this giant will bring some surprises, see you next week!
I just have a feeling that... it is much smarter. Not reflected by the common benchmarks, but it is just way better than the models before. This gives us much confidence in scaling, either model or data size.
Qwen3-Max-Preview (Instruct) biggest model yet from Qwen, with over 1 trillion parameters is now available in anycoder Benchmarks show it beats previous best, Qwen3-235B-A22B-2507 Voxel Pagoda garden, 1 shot [image]
Qwen3-Max, @Alibaba_Qwen's most powerful model is live on OpenRouter: 📊 Higher accuracy in math, coding, logic, and science tasks 📖 Stronger instruction following & reduced hallucinations 🔍 Optimized for RAG + tool calling (no “thinking” mode) [image]
Big news: Introducing Qwen3-Max-Preview (Instruct) — our biggest model yet, with over 1 trillion parameters! 🚀 Now available via Qwen Chat & Alibaba Cloud API. Benchmarks show it beats our previous best, Qwen3-235B-A22B-2507. Internal tests + early user feedback confirm: [image]