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Multiverse Computing raises $570M Series C funding at $1.7B valuation for AI model compression technology

Funding Confirmed 92% confidence first seen

Multiverse Computing, a Spanish startup specializing in AI model compression, closed a $570 million Series C funding round at a $1.7 billion valuation, co-led by Forgepoint Capital, Bullhound Capital, and BNP Paribas's Solar Impulse Venture Fund. The company's CompactifAI technology uses tensor network techniques to reduce large language model sizes by 50-95% while maintaining accuracy, enabling efficient inference on edge devices like smartphones and laptops. The funding will support expansion of the company's model library, R&D acceleration, and geographic expansion into Asia, the Middle East, and North America.

The deal

Deal terms as reported in the coverage below.

Decision brief

What changed
Multiverse Computing, a Spanish startup, closed a $570 million Series C funding round at a $1.7 billion valuation to scale its CompactifAI model-compression technology, which uses tensor network techniques to shrink large language models by 50-95% for edge deployment.
Why it matters
This signals growing investor conviction that AI inference is shifting from centralized cloud/data-center dependence toward edge devices (phones, laptops, drones), which could reshape infrastructure cost structures and vendor strategies for enterprises deploying AI at scale. A ~5x valuation jump from the prior round also indicates intensifying competition and capital concentration in the model-efficiency/compression segment, a category CTOs and CEOs should track when planning AI deployment architecture and vendor partnerships.
Affected roles
CEO CTO CFO COO
Evidence
Three independent outlets (Sifted, Tech.eu, SiliconANGLE) consistently report the $570M raise and $1.7B valuation with the same lead investors (Forgepoint Capital, Bullhound Capital, BNP Paribas SIVF), though Sifted's initial reporting cited a differing €500m/€2bn figure, suggesting the deal terms evolved or were reported at different stages.
What remains uncertain
The compression accuracy claims (50-95% size reduction with 'minimal accuracy loss') are sourced from company statements relayed by press, not independently benchmarked; the 5x valuation increase from the June 2025 round is asserted by one outlet without clear methodology, and real-world enterprise adoption or customer traction is not detailed in the coverage.
Monitor next
Watch for independent third-party benchmarks or enterprise customer deployments of CompactifAI-compressed models (e.g., Llama 3.3 70B on consumer hardware) that validate the compression claims outside company-provided data.

Analytical support, not advice — assumptions and open questions stated above.

Source coverage

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