Datasets:

hundredthrun
/

gpu-cloud-prices

license: cc-by-4.0
pretty_name: GPU Cloud Prices
task_categories:
  - tabular-regression
tags:
  - gpu
  - cloud
  - pricing
  - h100
  - b200
  - h200
  - a100
  - tabular
language:
  - en
size_categories:
  - 1K<n<10K
configs:
  - config_name: gpu_prices
    data_files: gpu_prices.csv
  - config_name: gpu_price_history
    data_files: gpu_price_history.csv
  - config_name: gpu_price_rows_daily
    data_files: gpu_price_rows_daily.csv
  - config_name: api_prices
    data_files: api_prices.csv
  - config_name: lead_times
    data_files: lead_times.csv
  - config_name: models
    data_files: models.csv

GPU Cloud Prices (H100, H200, B200 and more)

Public on-demand, spot and listed GPU rental prices from 25 cloud providers (H100, H200, B200, B300, GB200, GB300, A100, L40S, MI300X, MI355X), normalized to USD per GPU-hour. Every row links to the provider page it came from and records the date it was read.

Live tables, calculators and provider comparisons: https://hundredthrun-compute-desk.pages.dev
Open data docs on the desk: https://hundredthrun-compute-desk.pages.dev/open-data
Source repo: https://github.com/hundredthrun/gpu-cloud-prices
JSON API: https://hundredthrun-compute-desk.pages.dev/api/v1/prices.json
Kaggle mirror: https://www.kaggle.com/datasets/hundredthrun/gpu-cloud-rental-prices
Browse the cheapest price per GPU (Hugging Face Space): https://huggingface.co/spaces/hundredthrun/gpu-cloud-prices
Starter notebook (pandas, charts, price changes): https://github.com/hundredthrun/gpu-cloud-prices/blob/main/notebooks/gpu-cloud-prices-starter.ipynb

Files

File	What it holds
`gpu_prices.csv`	One row per provider, GPU and price type, with `source_url`, `date_checked`, `fetch_method` and `confidence`.
`gpu_price_history.csv`	Min, median and max price per GPU per daily snapshot (starts 2026-11-04).
`gpu_price_rows_daily.csv`	Every provider row as it stood on each snapshot date, so you can track individual price changes.
`api_prices.csv`	Sourced LLM API prices (USD per 1M input and output tokens) for open models, used by the desk's self-host vs API calculator.
`lead_times.csv`	Availability and lead-time notes as stated by providers.
`models.csv`	Open model parameter counts used by the desk's GPU memory calculator, with sources.

Load a config with:

from datasets import load_dataset
ds = load_dataset("hundredthrun/gpu-cloud-prices", "gpu_prices")
print(ds["train"][0])

Columns (gpu_prices.csv)

provider, gpu, variant, gpus_per_unit
price_usd_per_gpu_hr, price_type (on_demand / spot / preemptible / reserved), term, region, billing_unit
price_as_listed, derivation, availability_note, lead_time_class
source_url, date_checked, fetch_method, confidence, notes

Method

Prices are read from each provider's public pricing page or official price API. Multi-GPU node prices are divided by GPU count; the original wording is kept in price_as_listed. Confidence is high for API or itemized prices, medium for "starting at" prices, low otherwise. Unpublished values stay blank. Nothing is estimated.

Limitations

Public list prices only. Negotiated, reserved and committed-use prices are often lower. Check date_checked and the source before you buy.

Updates

Prices are re-checked daily. Dataset versions are pushed on the Tuesday refresh (and on demand). Price history charts: https://hundredthrun-compute-desk.pages.dev/history/

Card last rebuilt: 2026-11-09.

License

CC BY 4.0. Credit "Hundredth Run compute desk" with a link to https://hundredthrun-compute-desk.pages.dev