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Multiverse Computing Raises $215 Million to Scale Technology that Compresses LLMs by up to 95%

Multiverse Computing
Multiverse Computing
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Insider Brief

  • Multiverse Computing has raised €189 million ($215 million) to scale its quantum-inspired AI model compression tool, CompactifAI, which reduces large language model size by up to 95% without sacrificing performance.
  • CompactifAI enables 4x–12x faster processing and 50%–80% lower inference costs, making it possible to run advanced AI models on devices ranging from phones to Raspberry Pi.
  • The Series B round is backed by investors including Bullhound Capital, HP Tech Ventures, Forgepoint Capital, and Toshiba, supporting Multiverse’s push to transform the $106 billion AI inference market.

PRESS RELEASE — Multiverse Computing, the global leader in quantum-inspired AI model compression, has developed CompactifAI, a compression technology capable of reducing the size of LLMs (Large Language Models) by up to 95% while maintaining model performance. Having spent 2024 developing the technology and rolling it out to initial customers, the company today announces a €189 million ($215 million) investment round.

The Series B will be led by Bullhound Capital with the support of world-class investors such as HP Tech Ventures, SETT, Forgepoint Capital International, CDP Venture Capital, Santander Climate VC, Quantonation, Toshiba and Capital Riesgo de Euskadi – Grupo SPRI. The company has brought on widespread support for this push with a range of international and strategic investors. The investment will accelerate widespread adoption to address the massive costs prohibiting the roll out of LLMs, revolutionizing the $106 billion AI inference market.

LLMs typically run on specialized, cloud-based infrastructure that drives up data center costs. Traditional compression techniques—quantization and pruning—aim to address these challenges, but their resulting models significantly underperform original LLMs. With the development of CompactifAI, Multiverse discovered a new approach. CompactifAI models are highly-compressed versions of leading open source LLMs that retain original accuracy, are 4x-12x faster and yield a 50%-80% reduction in inference costs. These compressed, affordable, energy-efficient models can run on the cloud, on private data centers or—in the case of ultra compressed LLMs—directly on devices such as PCs, phones, cars, drones and even Raspberry Pi.

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“The prevailing wisdom is that shrinking LLMs comes at a cost. Multiverse is changing that,” said Enrique Lizaso Olmos, Founder and CEO of Multiverse Computing. “What started as a breakthrough in model compression quickly proved transformative—unlocking new efficiencies in AI deployment and earning rapid adoption for its ability to radically reduce the hardware requirements for running AI models. With a unique syndicate of expert and strategic global investors on board and Bullhound Capital as lead investor, we can now further advance our laser-focused delivery of compressed AI models that offer outstanding performance with minimal infrastructure.”

CompactifAI was created using Tensor Networks, a quantum-inspired approach to simplifying neural networks. Tensor Networks is a specialized field of study pioneered by Román Orús, Co-Founder and Chief Scientific Officer at Multiverse. “For the first time in history, we are able to profile the inner workings of a neural network to eliminate billions of spurious correlations to truly optimize all sorts of AI models,” said Orús. Compressed versions of top Llama, DeepSeek and Mistral models are available now, with additional models coming soon.

Per Roman, Co-founder & Managing Partner, Bullhound Capital, said: “Multiverse’s CompactifAI  introduces material changes to AI processing that address the global need for greater efficiency in AI, and their ingenuity is accelerating European sovereignty. Román Orús has convinced us that he and his team of engineers are developing truly world-class solutions in this highly complex and compute intensive field. Enrique Lizaso is the perfect CEO for rapidly expanding the business in a global race for AI dominance. I am also pleased to see that so many high-profile investors such as HP and Forgepoint decided to join the round. We welcome their participation.”

Tuan Tran, President of Technology and Innovation, HP Inc., commented: “At HP, we are dedicated to leading the future of work by providing solutions that drive business growth and enhance professional fulfillment. Our investment in Multiverse Computing supports this ambition. By making AI applications more accessible at the edge, Multiverse’s innovative approach has the potential to bring AI benefits of enhanced performance, personalization, privacy and cost efficiency to life for companies of any size.”

Damien Henault, Managing Director, Forgepoint Capital International, said: “The Multiverse team has solved a deeply complex problem with sweeping implications. The company is well-positioned to be a foundational layer of the AI infrastructure stack. Multiverse represents a quantum leap for the global deployment and application of AI models, enabling smarter, cheaper and greener AI. This is only just the beginning of a massive market opportunity.”

Multiverse Computing extends its sincere gratitude to its current investors for their continued trust and support, as well as to the European institutions whose backing has been instrumental in achieving this milestone. For more information about Multiverse Computing and CompactifAI, visit multiversecomputing.com

Matt Swayne

With a several-decades long background in journalism and communications, Matt Swayne has worked as a science communicator for an R1 university for more than 12 years, specializing in translating high tech and deep tech for the general audience. He has served as a writer, editor and analyst at The Quantum Insider since its inception. In addition to his service as a science communicator, Matt also develops courses to improve the media and communications skills of scientists and has taught courses. [email protected]

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