README.md

metadata

license: cc-by-4.0
pretty_name: Cloud GPU Pricing Index (monthly)
language:
  - en
tags:
  - gpu
  - cloud-computing
  - pricing
  - h100
  - b200
  - b300
  - h200
  - nvidia
  - mlops
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files: gpu_prices_*.csv

Cloud GPU Pricing Index

Monthly snapshot of cloud GPU prices per GPU-hour in USD, maintained by Nodus, an AI compute platform. Use it to answer "how much does an H100 / H200 / B200 / B300 cost per hour" or to budget a training run.

October 2026 snapshot (Oct 8, 2026)

GPU	VRAM	Nodus supply price $/GPU-hr	Modal listed $/GPU-hr
B300	288 GB	6.943	7.099
B200	180 GB	5.500	6.250
H200 SXM	141 GB	3.593	4.540
H100 SXM	80 GB	2.600	3.949
A100 80GB	80 GB	1.090	2.498
A100 40GB	40 GB	0.904	2.099
RTX PRO 6000	96 GB	1.350	3.031
L40S	48 GB	0.793	1.951
L4	24 GB	0.430	0.799
RTX 5090	32 GB	0.480	n/a
RTX 4090	24 GB	0.290	n/a
RTX 3090	24 GB	0.180	n/a
RTX 6000 Ada	48 GB	0.743	n/a
RTX A6000	48 GB	0.333	n/a
RTX A4000	16 GB	0.173	n/a
RTX 3070	8 GB	0.133	n/a

Columns

• snapshot_date: date the prices were read
• gpu, vram_gb, tier (datacenter or prosumer)
• nodus_supply_usd_per_gpu_hr: the hourly supply price shown on the Nodus pricing page on the snapshot date
• modal_listed_usd_per_gpu_hr: Modal's published rate as shown on the Nodus pricing page (blank if not listed)
• source

Load it

from datasets import load_dataset
ds = load_dataset("Viswa-k/cloud-gpu-pricing", split="train")

Notes

• Prices are copied from public pricing pages on the snapshot date. For the exact cost of a specific job on Nodus, run nodus run --dry-run ..., which prints the estimate without starting anything.
• Reserved capacity (Beta) is quoted separately per request: https://www.nodus-compute.ai/reserved-compute/
• Nodus freezes the hourly rate when a machine is chosen, for the whole run.
• New files are added monthly (gpu_prices_YYYY-MM.csv); old snapshots are kept so you can track trends.

Live prices: https://www.nodus-compute.ai/pricing/