Cerebras vs Graphcore

By valuation, Cerebras is the larger company at $8.1B versus $500M — a 16.2x difference. Size can also be measured by team: Cerebras employs 400 people while Graphcore has 500-1000 employees.

Cerebras has raised more in total funding at $1.8B, compared to Graphcore's $700M — a gap of $1.1B. Combined, the two companies have completed 10 known funding rounds.

Graphcore leads with an Awaira Score of 85/100, while Cerebras sits at 79/100. That 6-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Cerebras was founded by Andrew Feldman in 2016. Graphcore was founded by Nigel Toon in 2016. Visit each company's profile on Awaira for a full founder biography.

Cerebras: Cerebras Systems designs and manufactures specialized processors for artificial intelligence and machine learning applications. Founded in 2016, the company develops custom silicon chips optimized for training and inference of large language models and deep learning workloads. Its flagship product, the Cerebras Wafer Scale Engine (WSE), is one of the largest computer chips ever built, integrating hundreds of billions of transistors on a single wafer to deliver high compute density and memory bandwidth for AI workloads. The WSE architecture prioritizes parallel processing capabilities and reduced latency for neural network training, distinguishing it from traditional GPU-based approaches used by competitors like NVIDIA. Cerebras addresses the infrastructure layer of AI computing, targeting organizations training large-scale models. The company has secured substantial venture funding, indicating strong investor confidence in custom AI chip development. Cerebras has been pursuing an IPO and has attracted investment from firms including Tiger Global, Benchmark, and Altimeter Capital. Its competitive positioning centers on delivering superior compute efficiency and performance-per-watt compared to conventional accelerators. The company targets both cloud service providers and enterprises with significant AI computing requirements. Cerebras represents the emerging wave of AI-specific chip designers competing in the rapidly expanding AI infrastructure market, though adoption remains limited compared to established GPU manufacturers. Cerebras builds wafer-scale processors specifically engineered for large language model training, offering an alternative architecture to traditional GPU-based AI computing infrastructure. Graphcore: Graphcore designs the Intelligence Processing Unit, a processor architecture built specifically for machine learning workloads, offering a hardware alternative to NVIDIA GPUs for AI model training and inference. The Bristol-based company developed the IPU around a bulk synchronous parallel computation model that distributes model parameters across thousands of processor cores with local memory, achieving high efficiency for sparse and irregular neural network computations that GPUs handle inefficiently.\n\nThe company raised approximately $700 million across six funding rounds including a Series E that valued it at approximately $2.8 billion, with investors including Sequoia Capital, Microsoft, and Samsung Ventures. Graphcore processors are deployed in research institutions including Oxford, Cambridge, and the Rosalind Franklin Institute, as well as commercial AI platforms. The company has shipped multiple IPU generations including the MK2 IPU and Bow IPU, with the Colossus processor and IPU-POD system providing data centre scale AI compute.\n\nGraphcore competes directly against NVIDIA in the AI accelerator market, alongside AMD, Intel Gaudi, and other AI chip startups including Cerebras, SambaNova, and Groq. The AI accelerator market is projected to exceed $100 billion by 2027, driven by demand for model training compute. Graphcore faces the dominant position of NVIDIA and its CUDA software ecosystem as the primary barrier to adoption, requiring significant software investment to match the maturity of CUDA tooling that researchers and engineers have relied on for over a decade.

Both Cerebras and Graphcore launched in 2016. Same year, but even a few months' head start matters in AI — early movers lock in data, talent, and customer relationships fast.

Cerebras has about 400 employees; Graphcore has about 500-1000. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Cerebras and Graphcore compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.