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Wafer-Scale AI Training Supercomputers

Wafer-scale AI training chips are a revolutionary architecture that treats an entire wafer as a single processor, bypassing the interconnect bottlenecks of traditional multi-GPU setups. Cerebras and Tesla Dojo are the two major players in this space.

Mainstream Wafer-Scale Training Systems

ModelVendorTransistorsCoresOn-Chip SRAMCompute (FP16 Sparse)System ComputeStatus
Cerebras WSE-4 (CS-4, estimated)Cerebras~5 trillion~1,500,000~80GB~200 PFLOPS~200 PFLOPS2027 expected
Cerebras WSE-3 (CS-3)Cerebras4 trillion900,00044GB125 PFLOPS125 PFLOPS2024
Cerebras WSE-2 (CS-2)Cerebras2.6 trillion850,00040GB~62 PFLOPS~62 PFLOPS2021
Tesla Dojo ExaPODTesla18,000 billion (360× D1)127,440N/AN/A100 EFLOPs2023
Tesla Dojo CabinetTesla300 billion (6× D1 Tile)2,124N/AN/A~1.7 EFLOPs2023
Tesla Dojo D1Tesla50 billion354N/A36.7 TFLOPS (BF16)2022

Cerebras WSE-2 vs WSE-3 vs WSE-4 (Estimated)

MetricWSE-2 (CS-2)WSE-3 (CS-3)WSE-4 (CS-4, estimated)
ProcessTSMC 7nmTSMC 5nmTSMC 3nm
Transistors2.6 trillion4 trillion~5 trillion
Cores850,000900,000~1,500,000
On-chip SRAM40GB44GB~80GB
FP16 sparse compute~62 PFLOPS125 PFLOPS~200 PFLOPS
System TDP15 kW15 kW~30 kW
Release date202120242027 expected

Cerebras WSE Key Features

  • No memory wall: All data on-chip SRAM (no HBM)
  • Weight Streaming: Stream model weights to SRAM
  • No model parallelism: Single chip can train massive models
  • CS-3 system liquid cooled: 15kW TDP
  • Cluster option: Multiple CS-3s can be interconnected

Tesla Dojo Key Features

  • D1 single chip 354 cores: Custom architecture
  • 6 D1 = 1 Tile: High-density packaging
  • ExaPOD = 360 D1 = 100 EFLOPs: Single-cluster world leader
  • Purpose-built for FSD video training: Tesla custom
  • Not for sale: Tesla internal use only

Selection Guide

  • Large model research / pharma / materials science: Cerebras CS-3 (cloud rental via Cerebras Cloud)
  • Autonomous driving / video training: Tesla Dojo (Tesla internal only)
  • Cloud AI services: Cerebras Cloud accessible

Detailed Product Pages