Qualcomm partners with Multiverse Computing to shrink AI models without losing brainpower

Via foreignpolicyjournal.com

Quantum-inspired compression tech promises 93% faster response times and dramatically lower energy bills for data centers

by Editorial Team

Wed 5 Aug 2026 · 08:02 EDT 2 min read

In AI

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Qualcomm Technologies and Spain-based Multiverse Computing have teamed up to deploy compressed AI models on Qualcomm’s data center accelerators, a partnership that could reshape how efficiently large language models run at scale. The collaboration, announced on August 5, 2026, pairs Multiverse’s CompactifAI compression platform with Qualcomm’s Dragonfly AI200 and AI250 chips.

What the compression actually does

Multiverse’s CompactifAI platform uses what the company calls quantum-inspired tensor network compression. It borrows mathematical techniques from quantum computing to strip away redundant parameters in AI models, shrinking them significantly while preserving their accuracy.

The early results are genuinely striking. Compressed large language models running on Qualcomm hardware achieved response times up to 93% faster than their uncompressed counterparts. Performance improved by 44%, memory usage dropped by 45%, and energy consumption fell by 21%, all with no accuracy loss.

Prior deployments of Multiverse’s technology have delivered over 60% parameter reduction and 84% greater energy efficiency.

The two companies showcased these capabilities at MWC Barcelona 2026, where compressed models ran on Qualcomm’s Cloud AI100 Ultra hardware. That public demonstration apparently convinced both sides to formalize the partnership for broader commercial deployment.

The money behind the math

Multiverse Computing, founded in 2019 in San Sebastián, Spain, closed a $215 million Series B round in June 2025. As of late July 2026, it’s pursuing a Series C targeting up to $570 million at a pre-money valuation of $1.7 billion.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.

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