Single-GPU Inference v1.0.0
Validated infrastructure pattern
The smallest validated inference pattern: one accelerator serving a model on a single node, with storage for the weights, a security boundary, network ingress, a runtime and observability.
What it's for
Workloads this pattern servesComponents & topology
Layered by real dependency edges7 components, laid out top-to-bottom by their declared dependencies. Every edge is from the blueprint; GPUVerse does not add relationships that aren't there.
Tradeoffs & constraints
- Lowest cost and complexity, but no redundancy - a single node is a single point of failure.
- Bounded by one accelerator: the model plus its KV cache must fit in a single GPU (or a single multi-GPU node).
Data class
Curated · This is a stable architecture pattern from the blueprint registry. A concrete, costed deployment is generated per-request by the architecture engine from your model, provider and region - this catalog presents the pattern, not a fixed deployment.
This is a validated pattern from the architecture generator. Concrete cost, GPU sizing and provider bindings are produced when the engine generates a plan for a specific workload — they are not fixed attributes of the pattern, so they are not shown here as if they were.