snapshot_date stringdate 2026-10-08 00:00:00 2026-10-08 00:00:00 | gpu stringlengths 2 12 | vram_gb int64 8 288 | tier stringclasses 2
values | nodus_supply_usd_per_gpu_hr float64 0.13 6.94 | modal_listed_usd_per_gpu_hr float64 0.8 7.1 ⌀ | source stringclasses 1
value |
|---|---|---|---|---|---|---|
2026-10-08 | B300 | 288 | datacenter | 6.943 | 7.099 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | B200 | 180 | datacenter | 5.5 | 6.25 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | H200 SXM | 141 | datacenter | 3.593 | 4.54 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | H100 SXM | 80 | datacenter | 2.6 | 3.949 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | A100 80GB | 80 | datacenter | 1.09 | 2.498 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | A100 40GB | 40 | datacenter | 0.904 | 2.099 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | RTX PRO 6000 | 96 | datacenter | 1.35 | 3.031 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | L40S | 48 | datacenter | 0.793 | 1.951 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | L4 | 24 | datacenter | 0.43 | 0.799 | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | RTX 5090 | 32 | prosumer | 0.48 | null | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | RTX 4090 | 24 | prosumer | 0.29 | null | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | RTX 3090 | 24 | prosumer | 0.18 | null | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | RTX 6000 Ada | 48 | prosumer | 0.743 | null | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | RTX A6000 | 48 | prosumer | 0.333 | null | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | RTX A4000 | 16 | prosumer | 0.173 | null | https://www.nodus-compute.ai/pricing/ |
2026-10-08 | RTX 3070 | 8 | prosumer | 0.133 | null | https://www.nodus-compute.ai/pricing/ |
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 readgpu,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 datemodal_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/
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