Lambda Labs vs Graphcore

By valuation, Lambda Labs is the larger company at $4B versus $600M — a 6.7x difference. Size can also be measured by team: Lambda Labs employs 300 people while Graphcore has 500-1000 employees.

Lambda Labs has raised more in total funding at $2.3B, compared to Graphcore's $767M — a gap of $1.5B. Combined, the two companies have completed 6 known funding rounds.

Graphcore leads with an Awaira Score of 85/100, while Lambda Labs sits at 82/100. That 3-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Lambda Labs was founded by Stephen Balaban in 2012. Graphcore was founded by Nigel Toon in 2016. Visit each company's profile on Awaira for a full founder biography.

Lambda Labs: Lambda Labs is a cloud infrastructure provider specializing in GPU and AI computing resources, founded in 2012 and headquartered in the USA. The company operates a Series E funding stage with a valuation of $4.0 billion and has raised $2.3 billion in total funding. Lambda Labs provides on-demand cloud computing infrastructure optimized for machine learning, deep learning, and AI workloads, offering GPU instances, CPU resources, and storage solutions designed for researchers, enterprises, and AI practitioners. The platform enables users to access high-performance computing resources without significant capital expenditure, addressing the computational demands of training large-scale AI models. Lambda Labs competes in the AI infrastructure market alongside established providers like AWS, Google Cloud, and Microsoft Azure, as well as specialized competitors such as Lambda, Crusoe Energy, and CoreWeave. The company positions itself as an alternative to hyperscale cloud providers by offering specialized infrastructure optimized specifically for AI and machine learning workloads, potentially with competitive pricing and customer-focused service models. Lambda Labs serves various sectors requiring intensive computational resources, including academic research institutions, startups, and enterprise organizations developing AI applications. The company's growth trajectory reflects increasing demand for accessible, scalable AI computing infrastructure as organizations accelerate machine learning adoption. Its substantial funding and valuation indicate investor confidence in the expanding AI infrastructure market. Lambda Labs provides specialized GPU cloud infrastructure optimized for AI and machine learning workloads as an alternative to general-purpose hyperscale cloud providers. 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.

Lambda Labs got there first, launching in 2012 — that's 4 years of extra runway. Graphcore didn't arrive until 2016. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Lambda Labs has about 300 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 Lambda Labs and Graphcore compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.