NVIDIA GPUs with Confidential Computing are being used for confidential inference in Apple’s Private Cloud Compute as the service expands beyond Apple’s data centers to Google Cloud. Announced during Apple’s annual WWDC gathering for developers, the deployment will support server-side inference for Apple Foundation Models, which were custom-built by Apple and Google and use technologies behind the Gemini family of models.
NVIDIA is working with Apple and Google to support some next-generation Apple Intelligence features through NVIDIA Blackwell GPUs with Confidential Computing. The technology is integrated into Private Cloud Compute’s hardware security architecture running on Google Cloud, extending Apple’s privacy-focused cloud processing model beyond its own data centers while preserving controls for sensitive user requests.
NVIDIA Confidential Computing provides a hardware-based security layer for accelerated Artificial Intelligence workloads. It protects data while processing is underway by isolating workloads in trusted execution environments and allowing systems to cryptographically verify that infrastructure has not been tampered with before sensitive data is sent to a server. For end users, the intended privacy guarantee is that no one, including the system’s builders, can view their data, chats or conversations.
The move reflects a broader shift in Artificial Intelligence infrastructure as services combine on-device processing with cloud-based inference. NVIDIA frames Confidential Computing as a way to deliver high-performance server-side Artificial Intelligence processing while maintaining strong privacy and security guarantees for sensitive workloads.
Key capabilities include hardware-rooted trust to establish that systems are running on genuine, untampered NVIDIA GPUs, encrypted communication paths to protect data moving between components, remote attestation to verify a platform’s security state before releasing sensitive data, and support for accelerated Artificial Intelligence inference and training. These capabilities are positioned as increasingly important for Artificial Intelligence services that process sensitive information while maintaining strong user privacy controls.
