Lagrange-Labs/deep-prove

Health v2 · maintenance only

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3357 stars · 102 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

DeepProve is a Rust framework for generating zero-knowledge proofs of neural network inference, including end-to-end proving of full LLM forward passes using sumcheck and logup GKR protocols. It includes a core zkml proving library, a client stack with a proof-generation worker and CLI, tensor storage, and telemetry tooling.

Use cases

• prove that an LLM inference output came from a specific model
• generate zero-knowledge proofs of neural network forward passes
• verify ML model inference results without re-running the model
• benchmark zkML proving performance for GPT-2, Gemma 3, and Llama 2
• run a distributed proof generation network for AI inference
• quantize models and prove MLP, CNN, and transformer inference

When to choose

• you need cryptographically verifiable AI inference with succinct proofs
• you want the fastest available zkML proving for transformer/LLM models
• you need to prove inference of GPT-2, Gemma, or Llama models end-to-end
• you want GPU-accelerated or horizontally distributed proof generation

When to avoid

• you just need ML inference without verifiability
• you need a permissively licensed library (it uses a custom Lagrange License)
• your models are outside the supported MLP/CNN/transformer architectures
• you need tiny proof sizes or millisecond-level verification on constrained devices

Facets

framework · maturity active

machine-learning llm-inference cryptography sdk cli monitoring artificial-intelligence machine-learning large-language-models security developer-tools rust cli zkml zero-knowledge-proofs zk-snarks verifiable-inference sumcheck gkr transformers quantization prover-network cryptography linux gpu docker

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