Spanish artificial intelligence startup Multiverse Computing has secured $217 million in a Series B funding round, marking one of the sector’s most significant raises to date. The round was led by Bullhound Capital, an investor recognized for backing tech giants like Spotify, Klarna, Slack, Revolut, and Unity. Additional support came from HP Tech Ventures, SETT, Forgepoint Capital, CDP Venture Capital, Santander Climate VC, Toshiba, Quantonation, and Capital Riesgo de Euskadi - Grupo SPRI.[1][4]
The rapid adoption of large language models (LLMs) has drawn attention to a critical industry challenge: soaring computational and energy costs. Training leading LLMs may cost up to $5 million and require thousands of GPUs, causing infrastructure expenses to double annually. Multiverse Computing aims to solve this by drastically reducing the size and running costs of these models, without sacrificing performance.[1][2]
Central to the company’s breakthrough is its CompactifAI tool, which uses quantum-inspired tensor networks to compress the parameters of large AI models. Unlike traditional techniques like quantisation and pruning—which often lead to significant loss in model performance—CompactifAI can reduce a model’s size by up to 95% with negligible impact on output accuracy.[1][2]
Multiverse’s approach involves using tensor networks to identify and remove up to 80% of a model’s internal parameters—comparable to trimming unnecessary neural connections in the human brain. The reduced model is then retrained, delivering high-speed and energy-efficient inference, scaled for large enterprise and cloud deployments.[2]
With this funding, Multiverse Computing has increased its company valuation fivefold to over $500 million. The new capital will accelerate the global adoption of CompactifAI and support further research into quantum-inspired AI optimization. The company’s groundbreaking work could lower barriers for organizations worldwide, enabling faster, more cost-effective, and environmentally responsible AI deployment.[2][1]
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