Multiverse Computing has secured a substantial investment of €189 million ($215 million) to advance its cutting-edge technology, CompactifAI. This technology is designed to compress Large Language Models (LLMs) by up to 95%, offering significant efficiency gains without compromising performance. The company’s breakthrough enables faster processing speeds and substantial cost reductions in AI inference, allowing for the deployment of advanced AI models on various devices, from smartphones to Raspberry Pi.
The Series B funding round, led by Bullhound Capital and supported by prominent investors like HP Tech Ventures, Forgepoint Capital, and Toshiba, underpins Multiverse Computing’s mission to revolutionize the AI inference market, which is estimated at $106 billion. By addressing the challenges associated with running LLMs on cloud-based infrastructure, Multiverse Computing aims to drive widespread adoption of its compression technology, thereby reshaping the landscape of AI deployment.
CompactifAI, the brainchild of Multiverse Computing, represents a paradigm shift in model compression techniques. Unlike traditional methods that often compromise model performance, CompactifAI’s highly-compressed models retain accuracy while delivering significant speed enhancements and cost savings in inference processes. These compressed models can be deployed across various platforms, including cloud services, private data centers, and even consumer devices, marking a significant advancement in AI model deployment.
Enrique Lizaso Olmos, the Founder and CEO of Multiverse Computing, highlighted the transformative potential of CompactifAI in optimizing AI deployment and reducing hardware requirements. The technology’s unique approach, leveraging Tensor Networks inspired by quantum principles, allows for the efficient compression of neural networks, eliminating unnecessary correlations and optimizing AI models for enhanced performance.
Román Orús, Co-Founder and Chief Scientific Officer at Multiverse, emphasized the groundbreaking nature of Tensor Networks in streamlining AI models, enabling the development of highly efficient and accurate compressed versions of leading LLMs. Multiverse’s compression technology has already produced compressed iterations of renowned models like Llama, DeepSeek, and Mistral, with more innovations on the horizon.
Leading investors such as Bullhound Capital, HP Tech Ventures, and Forgepoint Capital recognize the disruptive potential of Multiverse Computing’s technology in enhancing AI processing efficiency and driving global competitiveness. The strategic significance of CompactifAI lies in its ability to democratize AI applications, making advanced AI capabilities accessible to businesses of all sizes.
Tuan Tran, President of Technology and Innovation at HP Inc., emphasized the alignment of Multiverse Computing’s innovation with HP’s vision of advancing AI applications at the edge. By investing in Multiverse, HP aims to facilitate broader adoption of AI technologies that offer enhanced performance, personalization, and cost efficiency, ultimately benefiting a wide range of industries.
Damien Henault, Managing Director at Forgepoint Capital International, underscored the transformative potential of Multiverse Computing in reshaping the AI infrastructure landscape. By enabling smarter, more cost-effective, and environmentally sustainable AI applications, Multiverse is poised to become a foundational player in the global AI ecosystem.
In conclusion, Multiverse Computing’s successful funding round and groundbreaking technology represent a significant milestone in the evolution of AI model compression and deployment. With a diverse group of investors backing its innovative approach, Multiverse is well-positioned to drive the next wave of efficiency and accessibility in AI applications, paving the way for a more democratized and sustainable AI ecosystem.
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