Multiverse Computing, headquartered in Spain, has closed a substantial €189 million Series B funding round led by Bullhound Capital. Multiple strategic investors participated in the round, including HP Tech Ventures, SETT, Forgepoint Capital International, CDP Venture Capital, Santander Climate VC, Quantonation, Toshiba, and Capital Riesgo de Euskadi. With this round, the company’s total funding now stands at approximately €250 million.
The new capital will propel the commercial rollout of Multiverse´s CompactifAI technology, a quantum-inspired solution tackling one of the most significant hurdles in the deployment of large language models: their immense infrastructure and computational demands. CompactifAI claims to compress large language models by up to 95% while maintaining performance—something traditional compression methods typically cannot achieve without major accuracy trade-offs. The method leverages advances in tensor networks, eliminating billions of superfluous correlations yet retaining core capabilities, enabling speedups and inference cost reductions of between 50% and 80%.
This breakthrough means that robust language models can now be deployed directly on edge devices—ranging from phones and PCs to cars, drones, and even tiny platforms like the Raspberry Pi—without requiring resources only available in the cloud or data centers. Compressed releases of models, including Llama, DeepSeek, and Mistral, are already operational and publicized by the company, opening pathways for broader application in diverse environments and industries.
Founded by Enrique Lizaso Olmos and chief scientific officer Román Orús, Multiverse Computing boasts an impressive 160 patents and a growing customer base with over 100 organizations, such as Iberdrola, Bosch, and the Bank of Canada. The company has received notable recognition, having been named by CB Insights as one of the Top 100 Most Promising AI Companies of 2025 and recently winning DigitalEurope’s 2024 Future Unicorn award. With new funding in hand, Multiverse Computing is poised to accelerate its global ambitions, aiming to reshape how organizations deploy language models and reduce the environmental and financial footprint associated with modern Artificial Intelligence technologies.
