X0NE-INFER
An inference engine that only runs inside an attested enclave. Whoever owns the machine sees neither your model, your prompts nor the answers.
the sequence, illustrated · machine without an enclave → intel tdx + nvidia h100, confidential mode
There is no other mode. Without a hardware proof, no port opens and no key is released.
The CPU and the GPU prove what they are, checked live with Intel and NVIDIA, before anything arrives.
Every answer comes with a signed receipt. You check it on your own machine.
Intel TDX with an NVIDIA H100 in Confidential Computing mode, 20 August 2026. Written in Rust by x0ne, in Paris. Version française.
An inference server that runs an AI model inside a hardware enclave (a TEE) and proves cryptographically, through remote attestation, that the enclave is genuine before it receives the model or the data. The machine's owner cannot read the model weights, the prompts or the answers.
Most confidential inference services place a stock engine such as vLLM inside a confidential VM: the same program can also serve outside an enclave. x0ne-infer has no such mode. Its attestation gate is a Rust type, so without a proof object nothing binds a socket or releases a key, and on a machine without an enclave the binary refuses to start. There is no development bypass.
It ran on real hardware on 2026-08-20: an Intel TDX machine with an NVIDIA H100 in Confidential Computing mode at a cloud provider, 10 min 23 s of billed machine, about $0.5. The CPU attestation is verified up to Intel's root and against Intel's live service, the GPU attestation through NVIDIA's production service, and the client re-verifies everything on its own machine.
A verified verdict means genuine confidential hardware answered this session's challenge. It does not yet mean that this exact binary is running: no launch measurement is pinned today. That is the next milestone, together with reproducible builds.
x0ne-infer is written in Rust by x0ne, in Paris. Its open-source release under Apache-2.0 is planned; the code is not public yet. Early access: contact@x0ne.co.