Nvidia has released fresh performance data showing that its newest artificial intelligence server can deliver up to 10 times boost in running advanced models, including two of the most widely used models developed in China. This update comes at a time when the global AI industry is shifting its focus from training models to deploying them at scale for millions of users.
The company’s latest results centre on mixture of expert models, a fast-growing technique that assigns different parts of a task to specialized experts within a model. This approach gained rapid traction after China’s DeepSeek introduced a high performing open source model in early 2025 that required less training on Nvidia hardware. Since then, the mixture of experts method has been adopted by OpenAI, Mistral and China’s Moonshoot AI, which launched a highly ranked open source model in July.
In its announcement, Nvidia emphasized that even though these models can be trained with fewer resources, its technology remains critical for serving them efficiently. The company said its newest AI server, which integrates 72 top tier chips connected through high speed links, boosted the performance of Moonshoot’s Kimi K2 Thinking model by 10 times compared with the previous generation of Nvidia systems. The same performance improvement was observed with DeepSeek’s models.
According to Nvidia, these gains are driven mainly by the ability to combine a large number of chips in one server and the strength of the links between them, areas where the company still holds an edge over its competitors. Rival AMD is also developing a similar multi chip server that is expected to reach the market next year.
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