Multiverse Computing Raises $570 Million Series C, Becoming AI Efficiency Unicorn at $1.7 Billion Valuation

Spanish artificial intelligence startup Multiverse Computing announced a $570 million (€500 million) Series C funding round on July 27, 2026, reaching a $1.7 billion pre-money valuation and becoming one of Europe's newest AI unicorns. The round represents a fivefold step-up from the company's Series B and signals growing investor appetite for technologies that make AI dramatically cheaper to run. For the latest AI industry coverage, this funding stands out as one of the largest European AI rounds of the year.

A Quantum-Inspired Approach to Model Compression

At the heart of Multiverse's platform is CompactifAI, a compression technology that applies tensor networks — a mathematical framework originating from quantum physics — to the problem of AI model compression. The technique was pioneered by co-founder and Chief Scientific Officer Dr. Román Orús and can reduce the size of large language models by 80 to 95 percent with what the company describes as immaterial accuracy loss.

The result is AI that runs faster, consumes less energy, and can be deployed in environments where sending data to a hyperscale cloud provider is too expensive, too slow, or simply not permitted. Multiverse positions its technology as the missing efficiency layer that lets enterprises run powerful models on their own infrastructure rather than routing every workload through a major cloud platform.

"The AI industry has accepted a false constraint for years — that powerful models require expensive infrastructure," said Enrique Lizaso, co-founder and CEO of Multiverse Computing. "That constraint is gone. We have proven that AI can run at full performance on a smartphone, inside a sovereign data center, on a factory floor with no cloud connection."

heavyweight Investor Lineup

The Series C round was co-led by Forgepoint Capital International, BNPP Solar Impulse Venture Fund, and Bullhound Capital. Additional commitments came from a broad consortium including Santander Alternative Investments, Tikehau Capital, HP Inc., Orange Ventures, Scania Invest, NAventures (the corporate venture arm of the National Bank of Canada), Qatar Development Bank, Zouk Capital, SETT, EIC Fund, the Basque Government's Hazten Scale-Up Fund, and Kutxa Fundazioa. The round was advised by JP Morgan and Santander CIB.

With prior rounds included, total funding is expected to reach approximately $800 million. The round may remain open to select additional strategic investors, the company said.

Per Roman, co-founder and managing partner at Bullhound Capital, framed the investment in distinctly European terms. "For years, Europe has worried it cannot compete at the frontier of AI," he said. "Multiverse is the answer — a team out of San Sebastián whose technology lets anyone run powerful models on their own terms, on their own soil, without depending on anyone else."

Explosive Revenue Growth and Real-World Deployment

Since closing its Series B in June 2025, Multiverse Computing has grown annualized revenue by more than 10x, with 96x year-over-year sales growth in the first quarter of 2026 alone. That trajectory places the company among the fastest-growing AI infrastructure businesses in Europe.

Multiverse's compressed models are already deployed across millions of devices and systems, including drones, cameras, satellites, vehicles, and telecom infrastructure. The company is also working to embed its technology into AI-powered personal computers. Its customer base of more than 100 organizations spans manufacturing, finance, energy, aerospace, cybersecurity, defense, and health and life sciences — including Allianz, Bank of Canada, Bosch, Iberdrola, Indra, PwC, and Telefónica.

Just days before the funding announcement, Multiverse disclosed that all CompactifAI-compressed models now run on Intel Xeon 6 processors, delivering what the company described as significant performance improvements, energy savings, and memory footprint reductions while preserving accuracy.

The CompactifAI Platform

Multiverse's platform spans the full deployment spectrum for efficient AI. Compressed models are optimized for cloud, on-premises, and on-device environments, orchestrated by the CompactifAI Router that decides in real time whether a given workload should run locally or be sent to the cloud. The company is also building an end-to-end software layer for next-generation AI factories and data centers that brings model compression, GPU orchestration, AI services, and sovereign-grade controls into a unified platform.

For enterprises, the pitch is straightforward: rather than replacing existing infrastructure or routing every workload through a hyperscaler, Multiverse adds an efficiency layer above it that matches each workload with the right model and backend — saving what the company claims can amount to hundreds of millions of dollars.

Damien Henault, managing director and partner at Forgepoint Capital International, called Multiverse "the only company we've seen that has both the technical foundation and the commercial traction" to serve as a critical AI infrastructure platform, noting its evolution from a downstream LLM compression tool into what he described as a complete AI foundry and operating system.

What the Funding Will Support

The Series C proceeds will fund the expansion of Multiverse's library of efficient models, continued research into proprietary compression algorithms, strategic investments in sovereign AI gigafactory infrastructure, and the establishment of a stronger regional presence in key markets including East Asia, Southeast Asia, the Middle East, Canada, and the United States.

The company is headquartered in Donostia (San Sebastián), Spain, with offices in the United States, Canada, and across Europe.

Why AI Efficiency Matters Now

The Multiverse raise arrives at a moment when the AI industry is confronting spiraling compute costs. Training and running frontier models requires enormous GPU clusters, and enterprises are increasingly searching for ways to deploy AI without incurring hyperscaler-level expenses. Model compression — reducing the computational footprint of large models while preserving their capabilities — has emerged as one of the most commercially important research directions in the field.

Yann Lagalaye, managing partner at BNPP Solar Impulse Venture Fund, emphasized the sustainability angle. "Beyond delivering substantial cost savings for its clients, Multiverse's solutions achieve a structural reduction in the energy intensity of LLM workloads through advanced model-compression techniques," he said, noting lower GPU utilization, reduced energy consumption, and decreased infrastructure requirements.

As the AI industry matures beyond the raw-capability race, companies that can deliver equivalent performance at a fraction of the cost may prove to be the most durable winners. With nearly $800 million in total funding and a growing roster of enterprise customers, Multiverse Computing is betting that efficiency — not just raw power — will define the next phase of artificial intelligence.

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