Cheapest H100 cloud price

The 2024–25 workhorse and still the default benchmark for training and high-throughput inference. Below: every cloud we track for the NVIDIA H100, ranked by price and last verified 2026-07-06 — so you rent 80GB of compute at the best rate, not the first one you find.

Cheapest
$1.65
Best provider
Vast.ai
Providers
18
Price spread
8.6×

NVIDIA H100

80GB · 18 providers tracked · verified 2026-07-06

Cheapest on-demand

$1.65/hr

ProviderTypeOn-demand $/hrSpot $/hr
Vast.aimarketplacecheapest
PCIe
$1.65
$0.91Rent →
Spheron
SXM
$2.01
$1.43Rent →
UpCloud
SXM
$2.08
Rent →
Sesterce
SXM
$2.09
Rent →
FluidStack
SXM
$2.10
Rent →
CUDO Compute
SXM
$2.25
Rent →
Lambda
SXM
$2.49
Rent →
Novita AI
SXM
$2.59
Rent →
RunPod
SXM
$2.69
Rent →
Nebius
SXM
$2.95
Rent →
OVHcloud
PCIe
$2.99
Rent →
Vultr
SXM
$2.99
Rent →
Gcore
SXM
$3.21
Rent →
DigitalOcean
SXM
$3.39
Rent →
Paperspace
SXM
$5.95
Rent →
AWS
SXM
$6.88
Rent →
Microsoft Azure
SXM
$6.98
Rent →
Google Cloud
SXM
$14.19
Rent →

Standard published on-demand pricing, USD per single GPU per hour, last verified 2026-07-06. Spot/marketplace and committed-use rates run lower. Hyperscaler rates are per-GPU from multi-GPU instance list prices. Spread on H100: 8.6× between cheapest and dearest tracked rate.

What the H100 really costs per useful hour

A rented GPU bills every hour it exists, not every hour it works. At the cheapest tracked rate ($1.65/hr at Vast.ai), here is the effective cost per hour of actual compute at real utilisation — the number that decides your bill.

25% utilised
$6.60/hr
50% utilised
$3.30/hr
75% utilised
$2.20/hr
100% utilised
$1.65/hr

Keep the card busy. A H100 idle two-thirds of the day costs 3× its headline rate per hour of work — utilisation, not the sticker, is the real price.

The H100 hyperscaler premium

The cheapest hyperscaler rate we track for the NVIDIA H100 is $6.88/hr (AWS) — 4.2× the specialist floor of $1.65/hr (Vast.ai). Identical silicon; the premium buys the platform, networking, and enterprise support bundled around it — worth it only if you actually need them.

What drives the H100 price gap

The NVIDIA H100 is identical silicon everywhere — the 8.6× gap between Vast.ai at the bottom and the hyperscalers at the top is about packaging, not performance. Specialist and marketplace clouds compete on raw $/hr; AWS, Azure and Google bundle the card with their platform, networking and support and price accordingly. For a sustained training run or a busy inference fleet, settling on the cheapest reliable provider is one of the largest single levers on your compute bill.

On-demand vs spot

On-demand guarantees the GPU is yours; spot and marketplace supply is cheaper but can be reclaimed, so it suits fault-tolerant or checkpointed workloads. Toggle "Best (incl. spot)" in the table above to see the cheapest available rate including interruptible supply.

Should you rent, or use an API?

If your goal is running an LLM rather than training one, renting a H100only beats a managed API above a breakeven volume — and the maths flips once you count idle hours. Check it first with the self-host vs API breakeven calculator.

Frequently asked questions

What is the cheapest cloud H100 price?

The lowest on-demand rate we track for the NVIDIA H100 is $1.65/hr at Vast.ai, across 18 providers (verified 2026-07-06). Spot and marketplace rates run lower with variable availability.

How much does an H100 cost per hour?

On-demand H100 pricing ranges from $1.65/hr to $14.19/hr per GPU depending on provider — about a 8.6× spread for the same card. Specialist clouds are cheapest; hyperscalers (AWS/Azure/GCP) sit at the top.

Is it cheaper to rent an H100 or use an LLM API?

Renting only wins above a breakeven volume, because a GPU bills every hour it exists while an API bills per token. Model your own crossover with the self-host vs API breakeven calculator before committing.

Independent comparison, no vendor influence. Standard on-demand pricing per single GPU, last verified 2026-07-06; negotiated and committed-use rates differ. Published under CC BY 4.0.

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