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Get hardware ids from list_hardware.","inputSchema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{"context":{"description":"Context length in tokens (default 8192).","maximum":1048576,"minimum":512,"type":"integer"},"hardware":{"description":"Hardware id or page slug, e.g. rtx-4090, mac-studio-m3-ultra-96gb.","type":"string"},"kv":{"description":"KV-cache quantization (default f16).","enum":["f16","q8_0","q4_0"],"type":"string"},"model":{"description":"Restrict to one model slug.","type":"string"}},"required":["hardware"],"type":"object"},"name":"find_fit"},{"description":"Median verified on-demand rental price per GPU class on Vast.ai (USD per hour), with min/p75 and offer counts, the collection timestamp, and per class the Rent Index: this week's median against last week and against the first week collected, a trend word, and the days excluded as marketplace glitches, plus RunPod's lowest posted on-demand price per class (a list price, not a median), Clore.ai's median for the same class (a second marketplace, never blended), and the AWS, Azure and Oracle Cloud pay-as-you-go list prices per GPU-hour, each with the instance type, VM size or bare-metal shape the price sits in (list prices, read four times a day, no statement about capacity). The index describes what prices did; it never forecasts.","inputSchema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{},"type":"object"},"name":"gpu_prices"},{"description":"Curated GPU and Mac profiles the fit engine knows — ids, memory, usable memory after margins, bandwidth. Use an id with find_fit.","inputSchema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{},"type":"object"},"name":"list_hardware"},{"description":"Daily price history per GPU class and source, up to 90 days: the rows the Rent Index and the 30-day range are computed from. Marketplace days (Vast.ai, Clore.ai) are medians over the day's counted hourly medians with min, p75 and offer count; list-price days (RunPod, AWS, Azure, Oracle Cloud, Lambda, Nebius, CoreWeave, Hyperstack) carry the posted price. Each row says which kind it is; never blend the two. Describes what prices did; it never forecasts.","inputSchema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{"days":{"description":"Days back from today (default 30, max 90).","maximum":90,"minimum":1,"type":"integer"},"gpu":{"description":"One class by slug or name, e.g. rtx-4090, h100. Every class without it.","type":"string"},"source":{"description":"One source key, e.g. vast, runpod, aws. Every published source without it.","type":"string"}},"type":"object"},"name":"price_history"},{"description":"Tracked AI models ranked by Heat Score (0–100, weighted percentiles of measured Hugging Face/OpenRouter signals) with the raw signals, local-run facts (GGUF size, quantization) and links. 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