The NVIDIA H100 NVL is an enterprise-class GPU built on the Hopper architecture, featuring 94 GB of memory. Currently available from 2 providers starting at $2.33/GPU/hour, with a market median of $2.60/GPU/hour across 3 configurations.
Hardware specifications
Same across all providers
Median price across all providers
5 offerings from 2 providers
Sorted by price ascending. Compare configurations side-by-side.
| Provider | Count | vCPU | RAM | Region | Per GPU hour | Total/hr | Action |
|---|---|---|---|---|---|---|---|
| ×1 | 18 | 206 GB | $3.190 | $3.19 | Launch | ||
| ×2 | 128 | 377 GB | From$2.330 -10.4% 30d | From$4.66 | Launch | ||
Up to$500credit | ×1 | 18 | 206 GB | $3.190 | $3.19 | Launch | |
Sesterce CloudReferral link | ×2 | 40 | 256 GB | -- | $3.476 | From$6.95 | |
OblivusReferral link | ×8 | 252 | 1.41 TB | $3.640 0.0% 30d | $29.12 | ||
| ×1 | — | — | -- | $4.200 0.0% 30d | $4.20 |
LLMs that fit on the NVIDIA H100 NVL
Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 94 GB per GPU. Showing the 12 largest that fit.
| Model | Parameters | 16-bit | 8-bit | 4-bit |
|---|---|---|---|---|
| DeepSeek V4 Flash DeepSeek | 284B | — Not released | — Not released | 192 GB Tight on 2× · 17% spare |
| Solar Open2 250B Upstage | 250B 15B active | 601 GB Too large | 330 GB Too large | 192 GB Tight on 2× · 17% spare |
| Qwen3 235B-A22B Alibaba | 235B 22B active | 564 GB Too large | 310 GB Too large | 181 GB 2× · 7.4 GB free |
| Laguna-S 2.1 Poolside | 118B 8B active | 282 GB Too large | 155 GB 2× · 33 GB free | 90 GB 1× · 3.7 GB free |
| gpt-oss-120b OpenAI | 117B 5.1B active | — Not released | — Not released | 78 GB 1× · 16 GB free |
| Qwen3.6 35B-A3B Alibaba | 35B 3B active | 86 GB 1× · 7.7 GB free | 47 GB 1× · 47 GB free | 28 GB 1× · 66 GB free |
| Qwen3 32B Alibaba | 32.8B | 79 GB 1× · 15 GB free | 43 GB 1× · 51 GB free | 25 GB 1× · 69 GB free |
| Gemma 4 31B Google | 31.3B | 75 GB 1× · 19 GB free | 41 GB 1× · 53 GB free | 24 GB 1× · 70 GB free |
| GLM-4.7 Flash Z.ai | 31.2B | 75 GB 1× · 19 GB free | 41 GB 1× · 53 GB free | 24 GB 1× · 70 GB free |
| Qwen3.6 27B Alibaba | 27.8B | 67 GB 1× · 27 GB free | 37 GB 1× · 57 GB free | 21 GB 1× · 73 GB free |
| Mistral Small 3.2 24B Mistral AI | 24B | 58 GB 1× · 36 GB free | 32 GB 1× · 62 GB free | 18 GB 1× · 76 GB free |
| gpt-oss-20b OpenAI | 21B 3.6B active | — Not released | — Not released | 17 GB 1× · 77 GB free |
Estimates: model weights plus 20% for KV cache and runtime overhead, at short context lengths. Long contexts and large batches need more. Rows marked “tight” hold the weights but not that full margin. A ×N figure is the total VRAM across N of these GPUs and makes no claim about interconnect throughput. How we estimate this · Start from a model instead
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