Hardware-Rooted AI Security That Won’t Slow You Down
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NVIDIA Confidential Computing (CC) secures AI inference workloads at the hardware level using Blackwell GPUs with a silicon-embedded private key, remote attestation via NRAS (supporting AMD SEV-SNP and Intel TDX), and encrypted NVLink interconnects. Benchmarks on HGX B300 running Qwen 3.5 397B at FP8 precision show CC adds only 2–8% overhead across throughput and time-per-output-token metrics at various concurrency levels. Performance optimizations include CC-safe autotuner timing in FlashInfer, async device-to-host copy workers in SGLang, and piecewise CUDA graph support to reduce kernel launch overhead amplified in CC mode.
Table of contents
Data, code, and model integrityOptimizing AI inference performance in Confidential ComputingBenchmark resultsTest SetupPath forwardResources131 Impressions