DeepProve breakthrough demonstrates verifiable AI keeps pace with frontier model innovation
SINGAPORE–(BUSINESS WIRE)–Lagrange Labs today announced at Google’s Zero-Knowledge event in Singapore that its platform, DeepProve, has successfully generated the world’s first cryptographic proof of Google’s Gemma3 large language model inference. This breakthrough demonstrates that cutting-edge AI architectures can be paired with cryptographic guarantees of correctness without sacrificing performance or innovation velocity.
The achievement marks a critical inflection point for AI and ZK, proving that zero-knowledge technology can adapt in real-time to the most advanced model architectures as they emerge from leading AI research labs.
“Gemma3 represents a clear departure from older GPT-style models with smarter attention mechanisms and novel optimizations,” said Ismael Hishon-Rezaizadeh, CEO and co-founder of Lagrange Labs. “By proving Gemma3, we’re demonstrating that verifiable AI isn’t a retrofit for yesterday’s models. It’s living infrastructure that evolves with the frontier of AI research.”
Technical Breakthrough: Proving Next-Generation Architecture
Gemma3’s advanced architecture presented significant cryptographic challenges that required fundamental innovations in DeepProve’s proving system:
- Group Query Attention (GQA): DeepProve adapted to Gemma3’s efficiency optimization that shares Key and Value tensors across multiple Query heads, requiring new proof structures for asymmetric attention patterns.
- Local + Global Attention: Unlike traditional models with consistent attention patterns, Gemma3 alternates between local sliding-window and global attention layers, demanding flexible attention masking proofs.
- Rotary Positional Encoding (RoPE): DeepProve implemented proofs for RoPE’s lightweight rotational encodings, achieving efficient scaling with sequence length compared to traditional quadratic approaches.
- RMSNorm Integration: With five to six RMSNorm layers per attention block, DeepProve built optimized proof circuits to maintain verification speed despite the architecture’s normalization density.
Industry Impact: Compliance Keeps Pace with Innovation
The successful proving of Gemma3 eliminates the choice between deploying cutting-edge models and meeting regulatory requirements. Healthcare systems can verify diagnostic models and process correct patient data, defense contractors can ensure mission-critical AI operates within defined parameters, and financial institutions can provide cryptographic receipts for AI-driven decisions.
“Organizations no longer need to choose between innovation and verifiability,” said Hishon-Rezaizadeh. “DeepProve on Gemma3 proves that compliance keeps pace with model upgrades.”
Production-Ready Verification at Scale
DeepProve’s Gemma3 integration builds on Lagrange’s production track record of over 11 million zero-knowledge proofs generated and 3 million AI inferences verified. The system maintains DeepProve’s 158x performance advantage over competing zkML solutions while supporting the most advanced model architectures.
“With DeepProve on Gemma3, proving AI correctness isn’t hypothetical anymore,” said Hishon-Rezaizadeh. “It’s cryptographically guaranteed.”
About Lagrange Labs
Lagrange Labs operates the universal ZK Prover Network on EigenLayer, providing cryptographic verification for AI, rollups, and cross-chain applications. With partnerships including NVIDIA, Intel, and AWS, Lagrange serves major enterprises requiring verifiable computation at scale. The company has raised $21.5 million from investors including Founders Fund and 1kx, and launched its LAG token in July 2025. Learn more at www.lagrange.dev.
About DeepProve
DeepProve is the fastest production-ready zkML system, enabling cryptographic verification of AI model inferences. With support for transformer architectures including GPT-2, LLAMA, and now Gemma3, DeepProve provides enterprises with mathematical guarantees of AI correctness without compromising privacy or performance.
Contacts
Media Contact: KCD PR for Lagrange Labs, [email protected]
