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Anthropic Unveils FlashProve to Cryptographically Verify AI Model Outputs

The open-source prototype uses a hash-based zero-knowledge proof to show a claimed model produced a response without exposing its private weights.

Overview

  • Anthropic published FlashProve as an open-source research prototype under Apache 2.0 that the company released on Tuesday, November 3, 2026.
  • The system requires an offline cryptographic commitment or fingerprint of model weights and then produces a per-inference hash-based zkSNARK that anyone can verify without seeing the weights.
  • Anthropic demonstrated the approach on Meta’s 400B-parameter Llama 4 Maverick and reported roughly 110 tokens per second on one NVIDIA H100, proofs of about 19 MB per 1,024 tokens, and CPU verification times around 17 to 21 seconds.
  • FlashProve currently carries large practical costs and limits: proving uses about 70–95 times the GPU time of standard vLLM inference, supports only up to 1,024-token contexts, and proves an integer model under greedy decoding rather than full floating-point or sampled outputs.
  • Anthropic and contributors published code, a protocol spec, and machine-checked formal proofs to invite researchers to cut proof size and compute overhead so the technique can be used for audits, anti-tampering checks, and regulatory verification.