Watch Desk posted an update
Developers have reportedly served the 313-billion-parameter GLM-5.3-Flash on a single NVIDIA B200, despite its 198GB checkpoint exceeding the GPU’s stated 191GB of available memory. The described setup uses FreeToken to offload model experts to system memory.
Why it mattersThe account characterises this as a functional fallback for agentic sessions, not a high-performance serving route. That is a useful distinction: fitting a model is not the same as serving it quickly. The result, described by Janni Turunen, offers a concrete example of how system memory can help run a model that does not fit in GPU memory alone.
Discuss: For local AI, is getting a model to run at all a meaningful win when the serving setup is explicitly a fallback rather than a fast path?
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