NVIDIA GPUs and each cloud's own silicon (AWS Trainium/Inferentia, Google TPU) traced through to the instance families built on them.
Second cloud in the 'where this hardware actually shows up' series — same shape as aws.json. Machine family → the silicon inside it (NVIDIA and Google's own TPU), plus the software integration points and what else on Google Cloud is neither. Verify current GA/allocation status before relying on it — the A3/A4 family is expanding quickly and access is often reservation-gated.
NIM microservices deployable through Vertex AI Model Garden and Google Kubernetes Engine.
NVIDIA's managed AI infrastructure service, also sold and run on Google Cloud capacity.
Google's AI Hypercomputer / Cluster Director large-scale training clusters use NVIDIA Quantum InfiniBand fabric alongside GCP's own Jupiter/Titanium networking stack.
The host/hypervisor offload and networking layer on modern Compute Engine GPU instances is Google's own Titanium architecture, not NVIDIA BlueField — the same distinction as AWS Nitro on EC2.
Google's custom Arm-based CPU (C4A and successors) is Google's own answer to general-purpose compute — a different lane from NVIDIA's Grace CPU, which pairs specifically with NVIDIA GPUs.
