Lambda Labs vs Cerebras

By valuation, Cerebras is the larger company at $8.1B versus $4B — a 2x difference. Size can also be measured by team: Lambda Labs employs 300 people while Cerebras has 400 employees.

Lambda Labs has raised more in total funding at $2.3B, compared to Cerebras's $1.8B — a gap of $480M. Combined, the two companies have completed 10 known funding rounds.

Lambda Labs leads with an Awaira Score of 82/100, while Cerebras sits at 79/100. 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. Cerebras was founded by Andrew Feldman 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. 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.

Lambda Labs got there first, launching in 2012 — that's 4 years of extra runway. Cerebras 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; Cerebras has about 400. 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 Cerebras compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.