Complete procedures with a way back.

Compare Ollama and vLLM without confusing a convenient local workstation runtime with a throughput-oriented serving engine. Reproduce model, request, hardware, batching, concurrency, multi-GPU, API, security, and operations evidence before choosing.

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.

Compare LM Studio and Open WebUI by role rather than treating them as interchangeable local AI applications. Test LM Studio as a model runtime/API and Open WebUI as a frontend that can connect to it or other backends, including multi-user identity and deployment choices.

Deploy an authenticated loopback service that uses Ollama through its OpenAI-compatible API, exposes only three compiled read-only host probes, records content-free audit evidence, runs under a hardened systemd account, and supports controlled backup, upgrade, rollback, and removal.

Build a bounded, repeatable compatibility suite for Ollama 0.32.0, LM Studio 0.4.1, and vLLM 0.23.0. The guide tests advertised models, non-streaming and streaming chat, strict structured output, forced tool calls, and the Responses endpoint while keeping provider documentation, locally measured evidence, and product positioning visibly separate.