Recommend the best (model x quantization x backend x GPU-count) deployment for a workload, or report why nothing fits. Returns candidates with per-number provenance (measured/extrapolated/estimated/unknown). Use for: 'what GPU do I need for ', 'will fit on ', 'how many GPUs for N req/s', 'what will it cost'.

Resolve a model id to real params/architecture (grounds hallucinated specs).

List known GPUs with VRAM/bandwidth/TDP/interconnect.

Compare self-hosting against the hosted APIs for a workload: sizes the cheapest feasible GPU fleet, prices the same traffic through each API model, and gives the monthly output-token volume where the two break even. Use for 'is it cheaper to self-host or use the API', 'when does a GPU pay for itself'. API prices come from a dated snapshot -- the result reports its age and flags it when stale; say so rather than quoting an old price as current.

Rank the models that actually fit and hit the SLO on a given GPU -- the inverse of planning. Use for 'what can I run on a 4090', 'best model for 12GB'. Sources: catalog (offline curated set), ollama (locally installed), hf (top Hub repos).