Rent an NVIDIA H100 SXM from $0.55 per GPU-hour
NVIDIA H100 SXM price per hour: $0.55 per GPU-hour on spot, $0.89 on-demand, $0.65 reserved, billed by the minute. The default choice for serious training and high-throughput inference: 80 GB of HBM3, 3.35 TB/s of bandwidth, full NVLink between the eight GPUs of a node, and FP8 support that roughly doubles usable throughput on models that tolerate it.
Billed per started minute. 640 GB of GPU memory on a 8× node. Persistent storage $0.08 per GB-month. No egress fees.
- GPU memory
- 80GBHBM3 · MIG capable
- Bandwidth
- 3,350GB/sSets token throughput on inference
- Node sizes
- 1× · 2× · 4× · 8×Same price per GPU at every size
- Reclaim rate
- <5%Spot instances reclaimed over 30 days
What you get with each H100 node.
| Node | GPU memory | vCPU | RAM | Local NVMe | Spot | On-demand | Action |
|---|---|---|---|---|---|---|---|
| 1× H100 | 80 GB | 26 | 240 GB | 2 TB | $0.55/h | $0.89/h | Configure |
| 2× H100 | 160 GB | 52 | 480 GB | 4 TB | $1.10/h | $1.78/h | Configure |
| 4× H100 | 320 GB | 104 | 960 GB | 8 TB | $2.20/h | $3.56/h | Configure |
| 8× H100 | 640 GB | 208 | 1,920 GB | 16 TB | $4.40/h | $7.12/h | Configure |
GPU-to-GPU link: NVLink 4, 900 GB/s; PCIe Gen5 128 GB/s. Local NVMe is scratch space wiped when the instance ends; keep anything you need on a persistent disk.
96 H100 GPUs free right now.
Straight from the capacity pool the console books against. Prices are identical in every region — pick the one closest to your data.
A region with zero free GPUs still accepts reserved capacity requests — we hold hardware for a term rather than sell what is already taken.
What fits in 80 GB — and what it costs per hour.
Weights need about 2 GB per billion parameters at FP16 / BF16, 1 GB per billion parameters at FP8, 0.5 GB per billion parameters at INT4. We keep 20% of the memory free for activations, the KV cache and the CUDA context, then take the smallest node that still fits.
| Open model | Parameters | FP16 / BF16node · spot price | FP8node · spot price | INT4node · spot price |
|---|---|---|---|---|
| Llama 3.1 8BThe default small model for fine-tuning and agents | 8B | 1× $0.55/h | 1× $0.55/h | 1× $0.55/h |
| Qwen3 14BMid-size dense Qwen3 | 14.8B | 1× $0.55/h | 1× $0.55/h | 1× $0.55/h |
| gpt-oss-20bSmall open-weight reasoning model for local and edge serving | 21B | 1× $0.55/h | 1× $0.55/h | 1× $0.55/h |
| Gemma 4 31BLargest dense Gemma 4, multimodal, 256K context | 31.3B | 1× $0.55/h | 1× $0.55/h | 1× $0.55/h |
| Qwen3.6 35B A3BSmall hybrid-attention mixture of experts | 35B | 2× $1.10/h | 1× $0.55/h | 1× $0.55/h |
| Llama 3.3 70BThe common 70B baseline (same size and layout as Llama 3.1 70B) | 70.6B | 4× $2.20/h | 2× $1.10/h | 1× $0.55/h |
| gpt-oss-120bOpen-weight reasoning model, mixture of experts, tool use | 117B | 4× $2.20/h | 2× $1.10/h | 2× $1.10/h |
| Qwen3 235B A22BFlagship Qwen3 mixture of experts, the 2507 checkpoint | 235B | 8× $4.40/h | 4× $2.20/h | 2× $1.10/h |
| DeepSeek R1Reasoning model, the R1-0528 checkpoint | 671B | over 8× | over 8× | 8× $4.40/h |
Each model links to its full sizing: KV cache by context length and every GPU that runs it — GPU requirements for 64 open models.
Real usage depends on context length, batch size and the serving engine: a long context can add tens of gigabytes of KV cache. Treat the table as the floor, not the ceiling — and if a job is close to the limit, take the next node size or quantise one step further.
What a dollar buys on an H100.
Ranked 20 of 21 data-center models in this catalogue on cost per gigabyte of GPU memory.
GPU memory you get for $1.00 of spot time, per hour.
Bandwidth decides token throughput far more often than raw FLOPS.
Spot price divided by published FP16 tensor throughput.
One GPU on spot, billed per minute, storage excluded.
Against the rest of the market
87 providers · September 2026- Median on-demand elsewhere
- $2.69Our on-demand is 67% below it
- Cheapest on-demand seen
- $1.15Our on-demand $0.89 is 23% below it
- Cheapest spot seen
- $0.69Our spot $0.55 is 20% below it
- 24 hours on one GPU
- $13.20 on spot$21.36 on-demand · $27.60 at the cheapest rate found elsewhere
Index built from published prices for the same GPU across 102 providers (provider pricing pages and public price indexes), September 2026. How the guarantee is enforced.
H100 SXM price per hour at 64 other providers.
The lowest published on-demand rate we recorded at each provider, cheapest first: $1.15 to $11.06 per GPU-hour, with a median of $2.50. Every row links to its source; a provider without a published price is left out rather than estimated.
| # | Provider | On-demandper GPU-hour | Spot | 730 h | Source |
|---|---|---|---|---|---|
| — | OnlineGPUthis site · how the price is set | $0.89 | $0.55 | $649.70 | pricing page |
| 1 | Compute Cheaprecorded 15 Sep 2026 | $1.15 | not published | $839.50 | computeprices.com |
| 2 | Liumrecorded 15 Sep 2026 | $1.30 | not published | $949.00 | getdeploying.com |
| 3 | Verdarecorded 15 Sep 2026 | $1.63 | $1.63 | $1,189.90 | shadeform.com |
| 4 | Latitude.shrecorded 15 Sep 2026 | $1.68 | not published | $1,226.40 | latitude.sh |
| 5 | Novita AIrecorded 15 Sep 2026 | $1.70 | $1.70 | $1,241.00 | getdeploying.com |
| 6 | Vast.airecorded 15 Sep 2026 | $1.73 | $0.69 | $1,262.90 | gpucloudcost.com |
| 7 | Gcorerecorded 15 Sep 2026 | $1.76 | not published | $1,284.80 | getdeploying.com |
| 8 | Cudo Computerecorded 15 Sep 2026 | $1.79 | not published | $1,306.70 | computeprices.com |
| 9 | HyperAIrecorded 15 Sep 2026 | $1.80 | not published | $1,314.00 | getdeploying.com |
| 10 | Beamrecorded 15 Sep 2026 | $1.83 | not published | $1,335.90 | getdeploying.com |
Recorded 15 September 2026 from published price pages (provider pricing pages and public price indexes), compute only: storage, egress and taxes excluded. Prices move — if a row is out of date, send us the link and it is corrected. The full table, with the monthly cost at every provider, is in the H100 price-per-hour guide.
What people run on an H100 SXM.
Training and full fine-tuning
Enough memory for optimiser states and activations on models a smaller card can only run in inference.
Serving large models
A 70B model at FP8 across two GPUs, with room for a long context window.
Multi-GPU jobs over NVLink
GPU-to-GPU traffic stays off the PCIe bus, which is what makes tensor and pipeline parallelism worth it.
Partitioned serving (MIG)
The GPU can be split into isolated instances, each with its own memory and compute slice.
NVIDIA H100 SXM, as published by NVIDIA.
Taken from the vendor datasheet. Where a figure is not published, the row is absent rather than estimated.
- Vendor
- NVIDIA
- Architecture
- Hopper (2022)
- Segment
- Datacenter
- Memory
- 80 GB HBM3
- Memory bandwidth
- 3,350 GB/s
- FP16 / BF16 tensor
- 990 TFLOPS
- FP8 tensor
- 1,979 TFLOPS
- FP32
- 67 TFLOPS
- Board power
- 700 W
- Form factor
- SXM5
- Interconnect
- NVLink 4, 900 GB/s; PCIe Gen5 128 GB/s
- Multi-instance (MIG)
- Supported by the GPU
- 8-bit float (FP8)
- Supported by the architecture
Source: www.nvidia.com · verified against the vendor document
Software that runs on it
8 templatesPre-built environments, pulled on the node before you land on it. Or bring any OCI image from a public or private registry.
On the spot tier
<5% reclaimed · 30 d- 2 minutes of notice on the metadata endpoint, a webhook and the console
- The instance is stopped, not deleted — disk and IP stay attached
- Auto-relaunch on the next free H100, or switch the same disk to on-demand
- You save $8.16 a day per GPU against on-demand
If the H100 is not the right fit.
Same memory or more, 11% cheaper on spot
H100 NVL 94 GB HBM3 · Hopper $0.49/h spotNext step up in memory: 94 GB instead of 80 GB
H200 SXM 141 GB HBM3e · Hopper $0.75/h spotSame Hopper generation
H200 NVL 141 GB HBM3e · Hopper $0.69/h spotSame Hopper generation
Or put two of them side by side: H100 vs GH200 · H100 vs H100 NVL · H100 vs H200
H100 SXM — the questions that come up
How much does an H100 SXM cost per hour?
Spot is $0.55 per GPU-hour and on-demand is $0.89, both billed per minute — every started minute costs the hourly price divided by 60, so $0.0092 on spot. Reserved capacity is $0.65 per GPU-hour on a monthly commitment. Storage and egress are not included in that rate: persistent disks are $0.08 per GB-month and there are no egress fees.
How many GPUs can I put in one instance?
Node sizes are 1×, 2×, 4×, 8× — up to 8 H100 SXM GPUs in a single virtual machine, with CPU, RAM and local NVMe scaled with the GPU count. The price per GPU is identical at every node size.
Can it run a 70B model?
Yes. At FP8, a 70B model needs about 70 GB for the weights, so it fits on 2× H100 SXM ($1.10 per hour on spot) with roughly 20% of the memory left for activations and the KV cache.
Which regions have it?
Available now in US East (Virginia), US West (Oregon), EU Central (Frankfurt). Prices are identical in every region; pick the one closest to your data.
How often is a spot H100 reclaimed?
Over the trailing 30 days, <5% of spot instances on this model were reclaimed. You get a 2-minute notice on the metadata endpoint, through a webhook and in the console; the instance is then stopped, never deleted, and the persistent disk stays attached.
Anything else about this model? Ask an engineer — the same people run the nodes. See also all prices, how we compare with 41 other providers and how to pay in crypto.
An H100 SXM for $0.55 an hour, running in under 60 seconds.
Prepaid in crypto, pay as you go: no card, no contract, no minimum commitment. Add credit, launch, stop whenever you want.
Billed per minute from the moment the instance is reachable. Minimum credit $30, no subscription. 96 H100 GPUs available right now.