Cerebras
Cerebras builds wafer-scale AI processors vastly larger than conventional chips for accelerated deep learning.
Updated April 2026
Overview
- Website
- cerebras.net
- Founded
- 2016
- Headquarters
- Sunnyvale, CA
- Segment
- GPU & AI Accelerators
Product overview
Cerebras develops Wafer Scale Engine (WSE) chips, like the WSE-3 with 900,000 AI cores and 44GB on-chip SRAM, integrated into CS-3 systems for AI training and inference. These massive single-wafer processors deliver extreme memory bandwidth (21 PB/s) and are used by enterprises, labs (e.g., Argonne, Mayo Clinic), governments, and cloud partners like G42. What distinguishes them from Nvidia GPUs is the wafer-scale integration eliminating multi-chip interconnect bottlenecks, enabling 2x+ faster inference on large models like Llama 4.
Revenue model
Primary: sales of high-end CS-3 AI systems (millions each) and supercomputer clusters to enterprises/governments; secondary: cloud inference (pay-per-token/subscriptions starting $10+), professional services.
Moat
Cerebras's key competitive moat is its proprietary wafer-scale engine (WSE) technology, which fabricates the world's largest monolithic AI chips spanning an entire silicon wafer with up to 4 trillion transistors, 900,000 cores, and 44 GB of on-chip SRAM, delivering unmatched on-chip memory bandwidth (21 PB/s) and fabric bandwidth (27 PB/s) that vastly outperform NVIDIA GPUs like H100 (52x more cores, 880x more on-chip memory) and even Blackwell (5x faster inference). This creates high barriers to entry through extreme technical complexity in manufacturing and assembly, patented innovations in on-wafer interconnects eliminating external networking overhead, and switching costs via the tailored Cerebras Software Platform for seamless PyTorch/TensorFlow integration on massive models.