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Cheap GPUs

by FastDrop

MCP Verified 2 hours ago Registry import free

Live GPU rental and LLM inference prices across dozens of providers, plus GPU price forecasts.

Live GPU rental and LLM inference prices across dozens of providers, plus GPU price forecasts. Official MCP Registry: com.cheap-gpus/cheap-gpus@1.0.0. Remote endpoint: https://cheap-gpus.com/mcp

Problem it solves

Discoverable MCP server listed in the official MCP Registry.

How it's different

Remote MCP endpoint ingested from the official registry and probed by FastDrop.

Ingested from the official MCP Registry

FastDrop pulled this entry from the official MCP Registry as com.cheap-gpus/cheap-gpus and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed and the description is not theirs.

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Tools this endpoint exposes

Read directly from the endpoint on 3 Nov 2026. Not supplied by the maker.

  • list_gpu_families

    List every GPU family tracked on cheap-gpus.com, with VRAM, live cheapest on-demand price (USD per GPU-hour), and how many providers currently offer it.

  • cheapest_gpu

    Cheapest current rental offers for one GPU family (e.g. "H100", "RTX 5090", "b200"), in USD per GPU-hour, cheapest first, one row per provider. pricing_type is "on_demand" (default; ca

  • gpu_price_history

    Daily price history for one GPU family: each day's median across providers of each provider's cheapest offer (USD per GPU-hour). days: 1-90.

  • find_model

    Search the LLM catalog by name (e.g. "deepseek v3", "gpt-oss", "llama 70b"). Returns model slugs to pass to cheapest_model_route / gpus_needed_for_model, most widely offered first. lim

  • cheapest_model_route

    Cheapest inference providers for one LLM (e.g. "deepseek-v3", "gpt-oss-120b"; use find_model if unsure of the name). Prices are USD per 1M tokens; estimated_cost_usd is for the given i

  • gpu_price_forecast

    Market-implied future rental price for one GPU family (USD per GPU-hour), from prediction markets (Kalshi, Polymarket) and ICE futures, plus today's compute-index benchmarks and cheap-

  • gpus_needed_for_model

    How many GPUs it takes to self-host an open-weight LLM at a given quantization, and the cheapest rental setups for it right now. quant is one of: fp16, bf16, fp8, mxfp8, int8, q6, fp6,

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Matched on shared tags and the tools their MCP servers actually expose.

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