GPU Economy - cloud GPU prices

io.github.laserodds21由 GitHub 帳號 laserodds21 發布v1.5.1更新於 Oct 27, 2026

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

已驗證Streamable HTTP可網頁執行雲端與基礎設施金融資料與分析

概覽

AI 產生的概覽

遠端 MCP 伺服器,提供 60 多家雲端 GPU 的每小時租賃價格,讓助理查找、比較、估算成本並追蹤 GPU 價格。

可以做什麼
  • 列出所有追蹤的 GPU 型號及其記憶體、供應商數量與隨需價格中位數,並依記憶體與價格條件篩選顯示卡
  • 查詢單一 GPU 或單一供應商的即時掛牌價格,由低到高排列,附讀取時間與來源頁面
  • 並排比較兩款 GPU 或兩家供應商,包含每 GB 記憶體價格與差額
  • 依顯示卡數量與小時數估算租賃成本,並將長期承諾或競價價格與隨需價格對比
  • 檢視價格趨勢:每週價格指數、價格歷史與近期價格變動
  • 依每百萬輸出 token 建模成本、比較購買與租賃,並搜尋與讀取 GPU Economy 頁面文字
適用情境
適合在挑選雲端 GPU 或供應商、為訓練或推論工作負載編列預算,或追蹤租賃價格走勢時使用。它回答的是目前掛牌價格與相對成本,而非實際可用容量。
執行需求
需要連線至 gpueconomy.com 的遠端 streamable HTTP 端點;未宣告任何套件、帳號、API 金鑰或環境變數。需要網路連線。
安裝前請注意
價格為掛牌價而非可用性;成本估算僅含租賃費,不含儲存、對外流量、稅金與閒置時間。Token 成本是依公開吞吐量建模而非實測。長期承諾無論是否執行都需付費。資料以 CC BY 4.0 發布,回答要求標註來源為 GPU Economy。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 GPU Economy - cloud GPU prices,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.laserodds21%2Fgpu-prices/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "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.

無需輸入參數。

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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數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.

輸入參數id必填

版本歷史

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

評分

已滿足適用檢查項的 83%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分

    請宣告包含 README 的 GitHub 儲存庫,或在 OAuth 受保護資源後設資料中提供 resource_documentation。

  • 授權條款不適用

    託管服務按其提供方的條款使用,因此這裡不要求授權條款。此檢查項不計入百分比。