Cerebras' approach to deploying large models across multiple wafers
The article's author uses open-source Kimi K3, with roughly 3 trillion parameters, to illustrate the approach.
TLDR
The article's author says a WSE-3T wafer has 44 GB of on-chip memory, while trillion-parameter frontier models need terabytes for their weights alone. Using Kimi K3 as an illustrative example, the article explains how Cerebras fits a full model into on-chip memory, maps it across multiple chips and handles many concurrent requests.
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