--- name: engine-picker description: Pick a self-hosted LLM engine (llama.cpp, Ollama, TGI, vLLM, SGLang) given hardware, scale, and workload. Name 2026 TGI maintenance mode as a migration trigger. version: 1.0.0 phase: 17 lesson: 28 tags: [self-hosted, vllm, sglang, llama-cpp, ollama, tgi, trt-llm, engine-selection] --- Given hardware (CPU / Apple Silicon / AMD / NVIDIA Hopper / NVIDIA Blackwell), scale (single-user / small team / production / enterprise), and workload (general chat / agentic / RAG / long-context / code), produce an engine recommendation. Produce: 1. Engine. Name the specific engine. Cite the hardware-first, scale-second, workload-third tree. 2. Why not the alternatives. For each alternative engine, state why it's not the pick (TGI maintenance mode, AMD excludes TRT-LLM, Ollama is dev-only). 3. Pipeline. If production, name the pipeline pattern (dev Ollama → staging llama.cpp → prod vLLM/SGLang) and confirm weight format (GGUF or HF) flows through. 4. Production stacking. At production scale, point to Phase 17 · 18 (production-stack), · 17 (disaggregated), · 11 (cache-aware router) for the composition. 5. TGI migration. If incumbent is TGI, specify the migration plan and timeline — not urgent but should start within 6 months. 6. Hardware gotcha. Call out the two hard constraints: CPU-only → llama.cpp; AMD → no TRT-LLM. Hard rejects: - Defaulting new projects to TGI in 2026. Refuse — maintenance mode. - Ollama for shared production at >1 concurrent user. Refuse — throughput gap. - Suggesting TRT-LLM without confirming NVIDIA-only. Refuse — AMD / non-NVIDIA is a hard block. Refusal rules: - If hardware is mixed (some AMD, some NVIDIA), require per-cluster engine decisions; do not force a single engine. - If the workload is "unknown/general" at production scale, default to vLLM and plan a re-evaluation after 3 months of traffic data. - If team wants "fastest per GPU without Blackwell availability" and insists on Hopper-only, confirm — TRT-LLM or vLLM are both acceptable. Output: a one-page recommendation with engine, alternatives dismissed, pipeline, production stacking, TGI migration posture. End with the single quarterly review: re-evaluate engine choice when workload shape changes materially.