GPU Economy - cloud GPU prices

io.github.laserodds21由 GitHub 账号 laserodds21 发布v1.5.1更新于 Oct 27, 2026

Hourly cloud GPU prices from 80+ providers: find, compare, cost and track GPUs.

已验证Streamable HTTP可网页运行云端与基础设施金融数据与分析

概览

AI 生成的概览

远程 MCP 服务器,提供 60 多家云 GPU 的每小时租赁价格,让助手查找、比较、估算成本并追踪 GPU 价格。

可以做什么
  • 列出所有被追踪的 GPU 型号及其显存、供应商数量和按需价格中位数,并按显存与价格条件筛选显卡
  • 查询单个 GPU 或单个供应商的实时挂牌价格,按价格从低到高排列,附读取时间和来源页面
  • 并排比较两款 GPU 或两家供应商,包括每 GB 显存价格和差额
  • 按显卡数量与小时数估算租赁成本,并将包年包月或竞价价格与按需价格对比
  • 查看价格趋势:每周价格指数、价格历史和近期价格变动
  • 按每百万输出 token 建模成本、比较购买与租赁,并搜索和读取 GPU Economy 页面文本
适用场景
适合在挑选云 GPU 或供应商、为训练或推理任务做预算、或追踪租赁价格走势时使用。它回答的是当前挂牌价格和相对成本,而非实际可用容量。
运行要求
需要访问 gpueconomy.com 上的远程 streamable HTTP 端点;未声明任何软件包、账号、API 密钥或环境变量。需要网络连接。
安装前请注意
价格为挂牌价而非可用性;成本估算只含租赁费,不含存储、出网流量、税费和空闲时间。Token 成本是基于公开吞吐量建模而非实测。包年包月无论是否运行都需付费。数据以 CC BY 4.0 发布,回答要求注明来源为 GPU Economy。

安装

在 SourceWeft 中

  1. 打开 控制台中的 GPU Economy - cloud GPU prices,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.laserodds21%2Fgpu-prices/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "gpu-economy-cloud-gpu-prices": {
      "type": "http",
      "url": "https://gpueconomy.com/mcp"
    }
  }
}

工具

16

list_gpus

List GPU models

Every GPU model tracked, with its id, VRAM, how many providers list it and the median on-demand rate card in USD per GPU-hour.

无需输入参数。

gpu_prices

Current prices for one GPU

Current listed rental prices for one GPU model across providers, cheapest first, in USD per GPU-hour, each with the time it was read and the GPU Economy page that links its source. Live quotes only.

输入参数gpu必填limitmarketregion

provider_prices

Current prices at one provider

Every current listed rental price at one provider (runpod, lambda, aws, vast-ai, ...), in USD per GPU-hour, each with its read time and the GPU Economy page that links its source. Live quotes only.

输入参数provider必填

price_index

Cloud GPU Price Index (H100)

The Cloud GPU Price Index: median listed on-demand H100 SXM rate across providers, this week and the last eight weeks, with the base-100 index and the receipts; also the newest hourly point and the monthly averages over a fixed panel.

输入参数window

recent_price_changes

Recent price changes

Listed prices that changed in the last 30 days, one row per quote, newest change first: the figure before its first change in the window, the figure now, and how many times it changed. A quote back at its starting figure is left out, and so are marketplace floors unless asked for. Optionally for one GPU or one provider.

输入参数gpulimitproviderinclude_marketplaces

find_gpus

Find GPUs that meet a requirement

GPU models that meet a memory and price requirement, cheapest first: for each card its cheapest live on-demand rate card (provider, read time, page), its median rate card and panel size, VRAM and price per GB of VRAM. Community capacity and marketplace floors are out unless the market is set.

输入参数limitmarketregionvendormin_vram_gbmax_usd_per_gpu_hour

compare_gpus

Compare two GPUs

Two GPU models side by side: VRAM, median rate card and panel size, cheapest on-demand rate, price per GB of VRAM, retail median where one exists, and every provider that lists both on-demand with the signed difference. Live quotes only.

输入参数a必填b必填

compare_providers

Compare two providers

Two providers on every GPU both list on-demand today: each side's cheapest on-demand rate card, the difference and which is lower, and the count. Community capacity and marketplace floors are left out of the comparison. Live quotes only.

输入参数a必填b必填

estimate_cost

Estimate what a workload costs

What N GPUs of one model cost for a number of hours at listed rates: at each of the cheapest rate cards and at the median rate card, with the arithmetic. Rental fee only - storage, network egress, taxes and idle time are not counted - and listed rates, not availability.

输入参数gpu必填gpushourslimitmarketregion

price_history

Weekly price history of one GPU

Weekly median and cheapest listed on-demand rate for one GPU model, newest week first, from two sources kept apart: our own hourly reads, and a series reconstructed from a public price catalog (second-hand). Each week carries its panel size; read a median against it.

输入参数gpu必填weeks

commitment_savings

What a 1- or 3-year commitment saves

Committed and spot rates for one GPU (or every GPU) set against the same provider's own on-demand rate for the same card, region and price scope - the pairs behind the site's typical discount - with the median per term across every card. A commitment is paid whether the GPU runs or not.

输入参数gputermlimit

provider_info

What a provider is and how it is read

One provider: its type (hyperscaler, specialist GPU cloud or marketplace), the regions or tiers it names, how GPU Economy reads its prices (pricing page, API or rendered page), how many GPU models and live quotes it has, a one-line note for a reader, its cheapest on-demand rate per card, and what it bills beyond the GPU-hour where read (what the rate includes, data out, storage, stopped instances, billing step). Links its GPU Economy page.

输入参数provider必填

token_cost

Cost per million output tokens (modelled)

Modelled, not measured: a listed GPU-hour rate divided by the output throughput NVIDIA published for that card and model, per million output tokens, at the cheapest live on-demand rate card and at the median, with NVIDIA's run (model, framework, precision, sequence, concurrency, date). Cards are not comparable on it - NVIDIA runs each card differently - and an idle GPU costs the same and produces nothing: a floor, never a bill.

输入参数gpu必填model

buy_vs_rent

Buy or rent a GPU

A card's new retail price (median of 3+ sellers) against its live on-demand rental rates: months of rental, at the cheapest rate card and at the median, that equal the purchase price, at 100%, 70%, 50% and 25% of a 730-hour month. Rental fee only - power, hosting, the server around the card and resale are not counted. Without gpu, every card that has a retail median.

输入参数gpu

fetch

Read a GPU Economy page

The text of one GPU Economy page by an id from search (gpu:h100-sxm, provider:runpod, index:h100, reserved, buy-vs-rent): its live rates with read times, as plain text, with the page URL to cite.

输入参数id必填

版本历史

3
  1. v1.5.1最新Oct 26, 2026
  2. v1.4.0Oct 1, 2026
  3. v1.0.0Sep 29, 2026

评分

已满足适用检查项的 83%

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  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分

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