# Hardware-Rooted AI Security That Won’t Slow You Down

[NVIDIA Developer Blog](https://yomu.fyi/company/nvidia-developer-blog) · Elizabeth Goodman · Jul 2, 2026

**Type:** Benchmark

## Summary

NVIDIA Confidential Computing secures enterprise data, proprietary model weights, and the model itself during active AI inference. The architecture integrates silicon-level private signing keys fused during manufacturing, encrypted multi-GPU NVLink, and remote attestation through the NVIDIA Remote Attestation Service alongside CPU Trusted Execution Environments. To mitigate overhead from secure work submission latency and encrypted host-to-device transfers, software optimizations incorporate CC-safe autotuner timing in FlashInfer, asynchronous copy workers in SGLang, and piecewise CUDA graph replay. Benchmarks on an HGX B300 system running the Qwen 3.5 397B-A17B model at FP8 precision show inference performance reaches up to 98% of non-confidential baselines across tested concurrency levels.

## Context

Concerns surrounding data privacy, sovereignty, and securing data while in use during inference impede enterprise AI adoption.

## Approach / What changed

NVIDIA implements Confidential Computing across Blackwell GPUs using fused hardware keys, remote attestation via NRAS with CPU TEEs, NVLink encryption, and software optimizations across FlashInfer and SGLang.

## Takeaways

- Blackwell GPUs utilize a factory-fused private signing key and remote attestation via NRAS to verify Trusted Execution Environments before deploying model decryption keys.
- Performance overhead in Confidential Computing stems primarily from secure work submission latency and reduced encrypted host-to-device CPU-to-GPU bandwidth.
- Benchmarking Qwen 3.5 397B-A17B on an HGX B300 with Intel TDX demonstrated throughput and median TPOT overhead within single-digit percentage deltas compared to baseline non-CC execution across multiple concurrency levels.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [LLMs](https://yomu.fyi/topic/llm), [Machine Learning](https://yomu.fyi/topic/machine-learning), [Performance](https://yomu.fyi/topic/performance), [Privacy](https://yomu.fyi/topic/privacy)

[Read original post](https://developer.nvidia.com/blog/hardware-rooted-ai-security-that-wont-slow-you-down)