Multiverse Computing Targets $570 Million Series C
Multiverse Computing announced on July 27 that it is targeting up to $570 million for a Series C at a $1.7 billion pre-money valuation. The round remains open to selected strategic investors, so it should not be treated as a completed $570 million raise. The company says the capital will expand its CompactifAI model-compression platform and support edge, cloud and sovereign AI deployments.
Multiverse Computing announced on July 27 that it is targeting up to $570 million (€500 million) for a Series C at a $1.7 billion pre-money valuation. The company named Forgepoint Capital International, BNPP Solar Impulse Venture Fund and Bullhound Capital as co-leads.
The transaction is not yet a closed $570 million financing. Multiverse's announcement says the round may remain open to selected strategic investors, while Sifted reports that it is in its final stages and still open. If completed at the stated amount, the company says its total funding, including earlier rounds, would reach $800 million.
Compression is the central product claim
Multiverse's CompactifAI platform applies tensor-network methods derived from quantum physics to compress AI models. The company claims the technology can reduce large language model size by 80% to 95% with minimal accuracy loss. Those figures are vendor-reported and the retrieved coverage does not provide an independent benchmark reproducing them.
Sifted reports that Multiverse is positioning compressed models for devices and infrastructure that cannot depend on hyperscale cloud resources. The company also describes a routing layer that can decide whether a workload should run locally or in the cloud.
What the company plans to fund
Multiverse says the proceeds would expand its model library, support proprietary algorithm research, fund software and infrastructure for sovereign AI deployments, and grow its presence in Asia, the Middle East, Canada and the United States. Cinco Días reports that the round includes commitments from public and private investors, including Spain's SETT, the EIC Fund, HP and Orange Ventures.
For ML teams, the financing matters because model compression is moving from a research technique into a product and infrastructure strategy. But the deployment decision remains workload-specific: practitioners still need to measure task accuracy, latency, memory use, energy consumption and hardware compatibility on their own models and target devices. The fundraising announcement establishes scale and investor interest; it does not independently validate the company's compression ratios.
Key Points
- 1The company is targeting up to $570 million at a $1.7 billion pre-money valuation, and the round remains open.
- 2Multiverse says CompactifAI can reduce LLM size by 80% to 95% with minimal accuracy loss, but the retrieved sources do not independently reproduce that claim.
- 3The proposed proceeds would support compressed-model development, sovereign AI infrastructure and expansion across Asia, the Middle East and North America.
Scoring Rationale
A targeted $570 million round at a $1.7 billion pre-money valuation is a major financing event for efficient AI infrastructure. The article preserves the important distinction between a target and a closed raise and treats the compression ratios as vendor claims.
Sources
Primary source and supporting public references used for this report.
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