CS

Cerebras CS-3 Inference Cluster (16-node)

cluster
16× WSE-3
On-wafer fabric per engine, 214 Pb/s; cluster networking via dedicated NET cabinets
2024
Power
475.0
kW Total
Memory
GB Total

A sixteen-node Cerebras inference cluster, provisioned as ten cabinets: eight WSE cabinets holding two CS-3 systems each, plus two NET cabinets. Provisioned heat load is approximately 475 kW, about 440 kW on water and 35 kW on air. That is Cerebras's own provisioned total including networking, not sixteen times the 27 kW system figure. The cluster holds 704 GB of on-chip SRAM and no DRAM. Each engine is rated at 125 petaFLOPS, footnoted by Cerebras as sparse; the sparsity is unstructured, so no dense figure is derived.

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System Details

GPU Configuration

GPU Model: Cerebras WSE-3
GPU Count: 16 GPUs
Architecture: Wafer Scale Engine 3
Interconnect: On-wafer fabric per engine, 214 Pb/s; cluster networking via dedicated NET cabinets

System Specifications

Form Factor: cluster
Total Power: 475.0 kW
Total Memory:
Memory Bandwidth: 336000000 GB/s

Powered by Cerebras WSE-3

This system utilizes 16 × Cerebras WSE-3 GPUs, each delivering exceptional performance for AI and HPC workloads.

Per GPU TDP

Per GPU Memory

Process Node

TSMC 5nm

Architecture

Wafer Scale Engine 3

Documentation & Resources

Official Datasheet

Cerebras CS-3 Inference Cluster (16-node) technical specifications

Download PDF

Cerebras CS-3 datasheet: system, rack and inference cluster specifications

Cerebras • Latest version

View Document ↗

Typical Use Cases

AI/ML Training
High-Performance Computing
Data Analytics

The Cerebras CS-3 Inference Cluster (16-node) runs 16× WSE-3 GPUs over On-wafer fabric per engine, 214 Pb/s; cluster networking via dedicated NET cabinets.