H100 SXM vs. H200 SXM: Which GPU Should You Choose?
We checked provider pricing and NVIDIA specifications to settle whether H100 SXM or H200 SXM is the better fit for your workload and budget.
Given the 0.44 on-demand price ratio, choose H100 SXM when the workload fits one GPU, choose H200 SXM when its larger memory capacity reduces the GPU count, with 7B full fine-tuning the key exception.
Before committing, check the live table to confirm that the on-demand minimums remain $1.74 for H100 SXM and $3.99 for H200 SXM.
Today's prices
USD/hr · 1× GPU · lowest on-demand price per provider
| Provider | H100 SXM | H200 SXM |
|---|---|---|
| Vast.ai | $1.74 | Not offered |
| Hyperstack | $3.20 · Not reported | $3.99 · Not reported |
| DataCrunch | $3.25 | $4.00 |
| RunPod | $3.29 | $4.59 |
| Crusoe | $3.90 · Not reported | $4.29 · Not reported |
| Together AI | $3.99 · Not reported | $5.99 · Not reported |
| Paperspace | $5.95 · Not reported | Not offered |
What your workload needs
Find your parameter count on the model's Hugging Face card. Serving maps to the inference rows, training to the fine-tuning rows.
| Workload | VRAM needed | H100 SXM | H200 SXM | Cheapest today |
|---|---|---|---|---|
| 70B Q4 inference | 42 GB | 1× $1.74/hr | 1× $3.99/hr | H100 SXM ×1 → $1.74/hr |
| 70B FP16 inference | 168 GB | 3× $1.74/hr | 2× $3.99/hr | H100 SXM ×3 → $5.22/hr (est.) |
| 70B QLoRA | 46 GB | 1× $1.74/hr | 1× $3.99/hr | H100 SXM ×1 → $1.74/hr |
| 7B full fine-tune | 112 GB | 2× $1.74/hr | 1× $3.99/hr | H100 SXM ×2 → $3.48/hr (est.) |
| 70B FP8 training | 154 GB | 2× $1.74/hr | 2× $3.99/hr | H100 SXM ×2 → $3.48/hr (est.) |
| Downshift recommendation | 42 GB | 1× $1.74/hr | 1× $3.99/hr | H100 SXM ×1 → $1.74/hr |
What the numbers say
H100 SXM carries an on-demand price ratio of 0.44 relative to H200 SXM, so it is the cost-first choice when either GPU can run the job on the same device count. Choose H200 SXM when its larger memory capacity reduces the number of GPUs required.
H200 SXM matches H100 SXM at the datasheet-based performance ratio of 1, which is a peak specification rather than measured application throughput. On that indirect basis, H100 SXM has an effective on-demand cost-per-job ratio of 0.44 versus H200 SXM, though actual results depend on the workload.
H100 SXM covers FP8, BF16, or FP32 workloads within 80GB VRAM, while H200 SXM supports the same precisions with a larger VRAM ceiling. The exception is a workload whose model state, activations, and runtime memory exceed the first ceiling but fit on one H200 SXM; choose H200 SXM when that headroom avoids a multi-GPU configuration, and choose H100 SXM otherwise.
Before you rent
Marlin matches your workload requirements to the lowest-priced suitable GPU across major cloud providers.
Source coverage is limited to the listed providers and vendor specifications, while prices and availability can change without notice. Workload costs and effective-cost comparisons are modeled from listed rates, VRAM formulas, and datasheet peak performance rather than measured end-to-end benchmarks. https://vast.ai/pricing · https://www.coreweave.com/pricing · https://www.hyperstack.cloud/gpu-pricing · https://www.together.ai/pricing · https://datacrunch.io/pricing · https://resources.nvidia.com/en-us-tensor-core/nvidia-tensor-core-gpu-datasheet · https://www.nvidia.com/en-us/data-center/h200/ · https://www.runpod.io/pricing · https://lambda.ai/service/gpu-cloud · https://crusoe.ai/cloud/pricing
Stop comparing. Start running.
Marlin matches your workload to the lowest-priced suitable GPU across supported providers.
Get started with Marlin