Classiq vs Graphcore

Graphcore has a disclosed valuation of $600M, while Classiq'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 Classiq's $63M — a gap of $704M. Combined, the two companies have completed 7 known funding rounds.

Graphcore leads with an Awaira Score of 85/100, while Classiq sits at 48/100. That 37-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Classiq was founded by Nir Minerbi in 2020. Graphcore was founded by Nigel Toon in 2016. Visit each company's profile on Awaira for a full founder biography.

Classiq: Classiq develops quantum computing software that automates the synthesis of quantum circuits from high-level algorithmic descriptions, allowing quantum algorithm developers to specify what computation should be performed without manually designing the low-level quantum gate sequences required to implement it. The Tel Aviv company platform generates optimised quantum circuits for specific hardware backends including IBM, Google, and IonQ quantum processors.\n\nThe company raised approximately $63 million in venture funding including a Series C from investors including HPE, NTT, and HSBC. Classiq targets financial services, pharmaceuticals, and logistics companies investigating quantum computing applications for optimisation, simulation, and machine learning, providing software tools that accelerate quantum algorithm development without requiring deep quantum physics expertise from application developers. The company has partnerships with IBM Quantum and NVIDIA cuQuantum for hybrid classical-quantum workflows.\n\nClassiq competes in the quantum software market alongside Qiskit (IBM), Cirq (Google), and commercial quantum software platforms including 1QBit and QC Ware. The company occupies the abstraction layer between algorithm description and hardware implementation, a segment that becomes increasingly valuable as quantum hardware matures and the bottleneck shifts from physical qubit availability to algorithm development productivity. The long timelines to commercial quantum advantage create both extended runway requirements and extended opportunity windows for quantum software infrastructure companies positioned ahead of hardware maturity. 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 4 years of extra runway. Classiq didn't arrive until 2020. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Classiq has about 1-50 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 Classiq and Graphcore compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.