Multiverse Computing Raises $570 Million at $1.7 Billion Valuation to Scale Efficient AI
Updated
Updated · GlobeNewswire · Jul 27
Multiverse Computing Raises $570 Million at $1.7 Billion Valuation to Scale Efficient AI
3 articles · Updated · GlobeNewswire · Jul 27
Summary
$570 million in Series C funding values Multiverse Computing at a $1.7 billion pre-money valuation, a 5x jump from its Series B and lifting expected total funding to $800 million.
CompactifAI underpins the raise by shrinking large language models 80% to 95% with limited accuracy loss, letting AI run faster and with lower energy use on devices, on-premises systems and sovereign data centers.
Multiverse said the capital will expand its efficient-model library, fund R&D, back sovereign AI infrastructure and software, and build out operations in East and Southeast Asia, the Middle East, Canada and the United States.
Since its June 2025 Series B, the Spanish company said annualized revenue has grown more than 10x, with Q1 2026 sales up 96x year over year, while its models are already deployed across millions of devices.
Could a Spanish scaleup's quantum trick to shrink AI by 95% finally break the global reliance on hyperscale cloud infrastructure?
Can Europe's €500 million bet on sovereign AI truly secure its digital borders and industrial secrets against foreign tech dominance?
Multiverse Computing Raises €500M to Lead Quantum-Inspired AI Compression and Edge AI for European Sovereignty
Overview
Multiverse Computing’s €500 million Series C funding in early 2026 marks a major step in Europe’s push for AI sovereignty. With strong backing from state and private investors, the company is expanding its quantum-inspired AI compression technology, CompactifAI, which can shrink large models by up to 95% with minimal accuracy loss. This allows powerful AI to run locally on everyday devices, reducing energy use and cloud dependence. Strategic partnerships and real-world deployments in sectors like energy and finance validate the approach, while the technology’s design also prepares AI models for future quantum hardware, ensuring long-term adaptability and global scalability.