Complete procedures with a way back.

Install and compare Ollama and LM Studio on one workstation using the same model, quantization, prompt, context, hardware, and bounded API harness. Separate GUI convenience, model management, GPU support, privacy, and headless automation from measured latency.

Integrate NVIDIA GPUs with Docker from a pinned driver/toolkit/CUDA matrix, assign devices by UUID or CDI, harden non-root workloads, monitor hardware with DCGM, and rehearse daemon-aware upgrades and rollback.

Deploy a pinned vLLM release behind a trusted TLS and authentication proxy, size GPU and KV-cache capacity from real workloads, isolate artifacts and listeners, verify quality and overload behavior, monitor the engine, and rehearse complete-bundle rollback.