QpiAI vs Graphcore

Graphcore has a disclosed valuation of $600M, while QpiAI's valuation is not publicly available, making a direct size comparison difficult. Graphcore employs 500-1000 people.

Graphcore has raised more in total funding at $767M, compared to QpiAI's $3M — a gap of $764M. Combined, the two companies have completed 4 known funding rounds.

Graphcore leads with an Awaira Score of 85/100, while QpiAI sits at 35/100. That 50-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

QpiAI was founded by Nagendra Nagaraja in 2019. Graphcore was founded by Nigel Toon in 2016. Visit each company's profile on Awaira for a full founder biography.

QpiAI: QpiAI develops a hybrid quantum-classical computing platform designed to accelerate AI and optimization workloads, combining quantum processing units with conventional AI accelerators. The company builds both quantum hardware prototypes and a software stack that abstracts quantum circuits for enterprise and research users in India.\n\nThe company raised approximately $3M in Seed funding and has partnered with national research institutions and defence organizations pursuing quantum-AI applications. QpiAI targets industries where combinatorial optimization problems — logistics routing, drug discovery, financial portfolio optimization — stand to benefit from quantum speedup.\n\nIndia's national quantum mission has allocated significant capital to domestic quantum computing development, and QpiAI is positioned as one of the few vertically integrated players with both hardware and AI software capabilities. As quantum hardware matures, the company's early investment in the full stack gives it a differentiated position in the emerging quantum-AI convergence market. QpiAI competes at the intersection of quantum computing and AI, a niche that remains largely experimental but is attracting increasing attention from enterprises exploring post-Moore's Law compute architectures. Its primary competitors include IonQ, Rigetti, and D-Wave in the quantum space, though QpiAI differentiates by focusing specifically on AI workload optimization rather than general-purpose quantum computing. Based in Bengaluru, the company is one of the few Indian startups operating in quantum-AI infrastructure, giving it a first-mover position in a domestic market where government investment in quantum research is accelerating through the National Quantum Mission. 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.

Graphcore got there first, launching in 2016 — that's 3 years of extra runway. QpiAI didn't arrive until 2019. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

QpiAI has about 10-50 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 QpiAI and Graphcore compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.