NVIDIA H100 SXM cloud GPU rental

The NVIDIA H100 SXM is a datacenter Hopper GPU with 80 GB of HBM3 at 3.4 TB/s of memory bandwidth. On FastInfra it is a good fit for 70B+ inference, multi-node training, large-batch fine-tuning. As a rule of thumb, one H100 SXM holds the weights of a model of about 32B parameters at 16-bit precision, or about 120B with 4-bit quantization, after leaving room for the KV cache.

Two on-demand tiers are available. Secure runs in vetted datacenters at $4.31 per GPU-hour; Value uses lower-cost community hosts at $2.91 per GPU-hour for the same GPU model, with more variable capacity.

Best for

70B+ inference, multi-node training, large-batch fine-tuning.

About the Hopper architecture

Hopper introduced the Transformer Engine with FP8 precision and fourth-generation NVLink at up to 900 GB/s per GPU. It is the most widely deployed architecture for LLM training and serving, and vLLM, SGLang, TensorRT-LLM, FlashAttention 3 and PyTorch are all tuned for it, so most open-source training and inference code runs at full speed without changes.

Only need inference?

If you want to call an open model such as Llama, Qwen, DeepSeek or GPT-OSS rather than manage a server, the pay-per-token inference API is often cheaper than keeping a GPU busy around the clock. It is OpenAI-compatible and uses the same account and wallet as your pods. Browse every model with live prices.

How much does it cost to rent an NVIDIA H100 SXM per hour?

$4.31 per GPU-hour on the Secure tier and $2.91 on the Value tier. Billing is per minute while the pod exists, so 24/7 use for a 730-hour month costs about $2,121 per GPU at the lowest on-demand rate. Prices sync from live capacity and are shown before you deploy.

How much VRAM does the NVIDIA H100 SXM have?

80 GB of HBM3 at 3.4 TB/s of memory bandwidth. The chip is rated at up to 700 W. A pod with 8 GPUs gives 640 GB of combined VRAM for tensor- or pipeline-parallel workloads.

What size LLM can I run on an NVIDIA H100 SXM?

Roughly 32B parameters at FP16 or BF16, 64B at 8-bit and 120B at 4-bit on a single GPU, reserving about 20% of VRAM for the KV cache and activations. Mixture-of-experts models need memory for all experts, not only the active ones. Long contexts and large batches need more headroom.

Is the NVIDIA H100 SXM billed per hour or per minute?

Per minute. The hourly rate is divided by 60 and charged for every minute the pod exists. Attached volumes bill per GB-month and continue while a pod is stopped; delete the pod to stop all charges. There is no minimum term or reservation fee.

How do I rent an NVIDIA H100 SXM on FastInfra?

Create an account, add prepaid credit, open the GPU configurator and choose the H100 SXM, the tier, the GPU count, a container template and storage. The configurator shows the hourly and monthly price, then deploys a pod you reach over SSH or JupyterLab within minutes.

Can I rent multiple H100 SXM GPUs in one pod?

Yes, up to 8 per pod (8 on Secure, 1 on Value). The price scales linearly: 8 GPUs cost $34.48 per hour on Secure.

Is there a cheaper GPU than the H100 SXM with the same VRAM?

Yes. The NVIDIA RTX PRO 6000 Max-Q has 96 GB and starts at $1.77 per hour. It differs in architecture (Blackwell), memory bandwidth and multi-GPU interconnect, so compare throughput for your workload before switching.