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Anthropic open-sources FlashProve, a prototype that can prove inference

3 reports3 sources2 days agoUpdated

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AI overview

Anthropic's Frontier Red Team released an open-source research prototype called FlashProve, which uses zkSNARKs to prove that a given response came from committed model weights without revealing weight information. The prototype is available on GitHub under the Apache 2.0 license, with the technical specification, part of the code, and Lean proofs. On Llama 4 Maverick (400B MoE), a single H100 achieves about 110 tokens/second, the proof size is about 19 MB, CPU verification takes about 17 seconds, and overhead is about 70 to 95 times that of normal inference. The prover requires one H100 80 GB, 24 CPU cores, and about 290 GB of host memory; the verifier uses only CPU and requires no GPU. Currently, the prototype supports only contexts of up to 1,024 tokens, greedy decoding, and MoE models, and cannot yet cover the random outputs commonly used by chatbots. Anthropic says the research is ongoing, there are no plans to deploy it at Anthropic or other labs, and the purpose of releasing it is for others to improve upon it.

AI overview based on source reports · Updated 2 days ago

Developments

2 developments

  1. Nov 4 06:41 · 1 reports
    Anthropic unveils model identity verification system FlashProve
    TechCrunch · AI:Anthropic is working on a system to prove AI models’ identity
  2. Nov 4 06:08 · 2 reports
    Anthropic releases FlashProve prototype that can prove inference
    MarkTechPost:Anthropic Releases FlashProve: Cryptographic Proofs That a Reply Came From Committed Weights

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Nov 4
  1. The Decoder
    Anthropic's new prototype proves which model wrote an AI response without exposing its weights

    Anthropic released FlashProve, an open-source research prototype that uses zkSNARK cryptography to prove a response came from a claimed model without revealing its weights. For Meta's 400-billion-parameter Llama 4 Maverick, it generates proofs at roughly 110 tokens per second on a single H100 GPU, with each ~19 MB proof verifiable in 17 seconds on a standard CPU, adding 70x to 95x overhead over normal inference. Anthropic notes the prototype only proves contexts up to 1,024 tokens, hides weights but not architecture, and works only when the model picks the single most likely next token rather than randomized sampling.

  2. TechCrunch · AI
    Anthropic is working on a system to prove AI models’ identity

    Anthropic is developing an open-source system called FlashProve that provides cryptographic "provable inference," letting users confirm that an output came from a specific model rather than an impostor. The system requires labs to publish model fingerprints that do not reveal private weights, and is designed to be lightweight enough for local verification. Researchers released a technical specification and open-source code on GitHub, but say the work is ongoing with no plans to deploy it at Anthropic or any other lab.

  3. MarkTechPost
    Anthropic Releases FlashProve: Cryptographic Proofs That a Reply Came From Committed Weights

    Anthropic's Frontier Red Team released FlashProve, an open-source zkSNARK prototype that proves a reply came from a committed model without revealing its weights, reaching about 110 tokens/second on Llama 4 Maverick (400B MoE) with one H100 and 18.78 MB proofs verified on a CPU in 17 seconds. Proving costs roughly 70 to 95x the GPU time of plain vLLM inference, and the system is currently limited to 1,024-token contexts, greedy decoding and MoE models. Security properties are formalized in Lean, with a cheating provider caught except with probability about q/2^124 + 2^-101.

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