Multiverse Computing raises $570M Series C at $1.7B valuation

2026-07-27

Spain-based Multiverse Computing raised $570 million in Series C funding at a $1.7 billion valuation to shrink large language models and cut energy and compute costs. The company uses quantum-inspired compression that it says can reduce LLM size by up to 95%, aiming at cheaper inference and edge deployment.

Key takeaway

Investor capital is concentrating on inference-cost reduction through model compression, not only on training ever-larger base models.

Context

Multiverse Computing is positioning compression as an economic lever: smaller models mean lower energy use and cheaper compute for operators who need specialized or edge deployments without full-scale hyperscaler budgets.

A $570 million Series C at a $1.7 billion valuation is a strong market signal that tooling to cut serving costs is now treated as strategic infrastructure, especially as builders weigh whether raw parameter count still dominates over deployability.

Numbers to know

$570MSeries C amount raised
$1.7Bcompany valuation at the round
95%claimed maximum LLM size reduction via compression

LLMgram editorial selection and synthesis · @llmgram. LLMgram is not the original publisher of this information.

Continue on LLMgram: Open in AI Signal →

Original reporting: Spain-based Multiverse Computing, which shrinks LLMs to reduce energy and compute costs, raised a $570M Series C at a $1.7B valuation (Amelia Isaacs/Pathfounders)