Alibaba’s Qwen3.8 model goes live on Nvidia’s GB300, hits 4,000 tokens per second

Alibaba just put the global AI leaderboard on notice. The company’s Qwen team launched Qwen3.8-Max on August 3, a massive 2.4 trillion parameter model that runs at over 4,000 tokens per second per GPU on Nvidia’s GB300 NVL72 hardware. To put that speed in perspective, 4,000 tokens per second per GPU means the model can generate roughly 3,000 words of text every single second on a single chip. What Qwen3.8-Max actually is The model operates as a sparse Mixture-of-Experts system, a design pattern where only a fraction of the model’s total parameters activate for any given input. Of its 2.4 trillion total parameters, approximately 95 billion are active per token. Qwen3.8-Max handles text, images, and video natively as a multimodal system. It also supports a context window of 1 million tokens, which translates to roughly 750,000 words of input. On the OSWorld-Verified benchmark, a test designed to measure how well AI models can autonomously complete computer tasks, Qwen3.8-Max scored 86.1. That places it ahead of both Anthropic’s Claude Fable 5 (85.0) and OpenAI’s GPT-5.6 Sol Max. It ranks as the second highest-performing AI model overall behind Fable 5 on broader evaluations. The mode...