Choose one supported backend and verify a minimal API request before installing more model types. Match model size and quantization to the available hardware, then test concurrent requests using realistic inputs. Keep the service behind appropriate authentication when making it available beyond a single machine.
This is best suited to self-hosted model inference for applications. Before committing a larger project, account for these trade-offs: backend setup varies by model; hardware determines throughput.
