Cerebras

Cerebras Systems is an AI hardware company founded in 2016, known for building the world's largest computer chips. The company's Wafer-Scale Engine (WSE-3) is a single chip that occupies an entire silicon wafer — containing 4 trillion transistors and 900,000 AI-optimized cores, making it roughly 50 times larger than the largest GPU.

Cerebras's CS-3 systems using the WSE-3 are designed for AI training and inference workloads that benefit from massive on-chip memory and bandwidth, eliminating the communication bottlenecks that occur in multi-GPU clusters. The company also operates Cerebras Inference, a cloud service offering some of the fastest inference speeds available — delivering over 1,800 tokens per second for Llama models, significantly faster than GPU-based alternatives.

Cerebras raised approximately $2.9 billion across 8 rounds privately before going public in May 2026, completing the largest US tech IPO of the year: 28 million shares priced at $185 (above the $115 to $160 range) for roughly $5.5 billion in proceeds, with the stock more than doubling on debut to close at $311 for a $66 billion market cap. The S-1 named OpenAI, Group 42, Saudi Arabia's MBZUAI (Mohamed bin Zayed University of Artificial Intelligence), and Amazon Web Services as top customers, and Cerebras swung to profitability on $510 million of 2025 revenue. OpenAI is one of Cerebras's largest customers under a multi-year contract worth more than $10 billion signed in January 2026, and holds a $1 billion secured loan plus warrants for over 33 million shares — making OpenAI a meaningful post-listing shareholder. The unconventional approach to AI computing challenges the dominant NVIDIA GPU paradigm, offering an alternative architecture that excels at high-bandwidth answer-inference workloads where on-chip SRAM gives Cerebras a practical latency advantage over HBM-based GPUs. Other major customers include AWS, Meta, Mistral, Perplexity, Mayo Clinic, US defense agencies, and pharmaceutical and research labs that need extreme computational throughput.