Cerebras Deploys Trillion-Parameter AI Models

Cerebras is deploying trillion-parameter AI models on its wafer-scale chips, addressing the challenge of memory requirements. A single Cerebras WSE-3T wafer has 44 GB of on-chip memory, while trillion-parameter models need terabytes for their weights. To overcome this, Cerebras uses a distributed approach where multiple wafers collaborate, with each wafer processing specific model layers and passing activations to the next, until the final wafer generates the output token.

This report details how Cerebras is deploying trillion-parameter models by distributing layers across multiple wafers, unlike other approaches that might focus on single-chip scaling.