FirstQFM® Outperforms Leading Classical Forecasting Models with Quantum-Powered System at ISC 2026, built with NVIDIA CUDA-Q
STOCKHOLM, SWEDEN, June 22, 2026, 09:00 AM CET.
FirstQFM, a pioneer in machine learning foundation models for quantum computing, announces a significant milestone in the commercial application of quantum computing today at the ISC High Performance conference. Built on NVIDIA accelerated computing, FirstQFM's Quantum Reservoir Computing system delivered a 56.1% series-level win rate against the strongest classical foundation-model baseline in zero-shot forecasting evaluation.
The breakthrough demonstrates the power of FirstQFM’s Quantum Foundation Models (QFM) when integrated with NVIDIA’s quantum computing platform. In rigorous benchmarking of financial time series, FirstQFM’s QRC model delivered superior directional accuracy and lower forecast error than leading classical time series foundation models, marking a pivotal moment for near-term quantum utility at scale.
Unlocking the "NISQ" Era with Quantum Foundation Models
While the industry has historically focused on future fault-tolerant systems, FirstQFM is already delivering production-ready results on today’s Noisy Intermediate-Scale Quantum (NISQ) hardware. By utilizing patent-pending, device- and problem-aware reservoirs, FirstQFM’s Quantum Reservoir Computing (QRC) solution targets high-value use cases on near-term systems and establishes a foundation for continued performance gains as quantum hardware advances.
"Building QRC on top of our proprietary quantum foundation models enables us to generate reservoirs that are both device-aware and problem-aware," said Vish Ramakrishnan, CEO and Co-Founder of FirstQFM. "That is what allowed us to outperform state-of-the-art AI forecasting models developed by teams at major technology companies, including Google, Salesforce, and Amazon. We believe this can become one of the first commercially viable applications of quantum computing."
Scaled on the Leonardo Supercomputer
The development and scaling of FirstQFM’s models were powered by NVIDIA CUDA-Q, NVIDIA cuQuantum, and NVIDIA cuTensorNet. FirstQFM optimized its workflows for training on the Leonardo Supercomputer, one of the world's most powerful systems, accelerated by NVIDIA infrastructure.
For enterprise "on-premises" deployments, the solution will leverage NVIDIA NVQLink, which provides the critical low-latency and high-throughput connection between GPU-enabled servers and quantum processors required for real-time inference.
Rigorous Validation
To ensure the performance gains were robust, FirstQFM employed a strict evaluation protocol: zero-shot forecasts on series excluded from the training set, ensuring that the results were not contaminated by data leakage or overfitting.
"The objective was to demonstrate gains over state-of-the-art zero shot forecasting systems on a selected set of tasks with commercial relevance," said Isaiah Hull, CTO and Co-Founder of FirstQFM. "To ensure the performance gains were robust, we designed the training set and evaluation protocol to avoid data leakage and overfitting, benchmarked zero-shot forecasts against zero-shot forecasts, and tested against some of the strongest forecasting systems available. NVIDIA's CUDA-Q platform and its GPU acceleration were indispensable to the project."
A Dual Go-To-Market Approach
FirstQFM is moving forward with a versatile Go-To-Market strategy that includes both cloud-based and on-premises business models. This flexibility allows enterprises to integrate quantum-enhanced forecasting into existing infrastructure and gain a decisive edge in forecasting.
About FirstQFM
FirstQFM is a Stockholm-based quantum technology startup specializing in the development of foundation models that improve the performance and scalability of quantum computers. By developing models that understand the nuances of specific quantum processors, FirstQFM enables the deployment of high-performance, commercially viable applications for the NISQ era and beyond. For more information, visit www.firstqfm.com.
Technical blog
For a detailed technical discussion of the Quantum Reservoir Computing system, benchmarking methodology, NVIDIA CUDA-Q integration, and forecasting results, read our accompanying technical article:
