Press & data kit

Price of Compute is the free reference for what compute costs: GPU rental prices across 16 cloud providers normalized to USD per GPU-hour (collected hourly, published as cross-provider daily medians), verified LLM token prices for 20 models, and a composite index. Methodology public, history free to January 2023, no login anywhere. Built and run by Noah Flanary.

Numbers you can print today

The Price of Compute Index: 127.5 (daily close, base 100 = 2026-08-10)
NVIDIA H100 SXM median: $3.93/GPU-hr across 10 providers ($1.99–$11.68)
Widest same-GPU spread today: NVIDIA H100 SXM at 5.9× between cheapest and priciest provider
History depth: daily series to 2023-01 on covered SKUs (archival reconstruction from dated Internet Archive snapshots, labeled, never estimated)

Scheduled price events we will record

2026-09-01: Claude Sonnet 5 intro pricing ends ($2/$10 → $3/$15 per MTok) — a rare published price increase, timestamped on our events feed.
Date TBA: DeepSeek has pre-announced a “significant” API price increase in its own docs — we track the before/after.

Embeds & assets

Live badges (hotlink freely): priceofcompute.com/api/badge/index.svg and /api/badge/h100-sxm.svg (any SKU slug). OG chart cards: /og?sku=h100-sxm. Logo: /logo.svg · lockup. Full data via the free API (JSON + CSV; 1,000 req/day/IP).

How to cite

All data here is free to use with attribution — in articles, papers, dashboards, products, and AI-generated answers. The one requirement:

Data: Price of Compute — priceofcompute.com

Formats

Prose / journalism

according to Price of Compute (priceofcompute.com), the median H100 rental price …

Academic

Price of Compute. "GPU rental and LLM token price dataset." priceofcompute.com, accessed <date>. https://priceofcompute.com

BibTeX

@misc{priceofcompute2026,
  title        = {Price of Compute: GPU rental and LLM token price dataset},
  howpublished = {\url{https://priceofcompute.com}},
  year         = {2026},
  note         = {Accessed: <date>}
}

For machines

Orientation files for AI assistants: /llms.txt and /llms-full.txt (the latter includes current values). Endpoints: /api/v1/openapi.json. Every API response carries an attribution field. Events feed: RSS. Method and rules: methodology.

Contact

Contact — data pulls, custom cuts, and interviews are fast; every observation stores its raw source payload, so any number can be traced end-to-end on request.