🔌
New: connect Claude & other AIs to GenAIList over MCP — research the catalog and contribute to the shared knowledge base. Learn how →
// RUN ON DATACENTER GPU
Run Wan 2.2 14B S2V on Datacenter GPU hardware
10 options with enough VRAM (FP16), ranked by headroom.
| Hardware | VRAM | Fits FP16? | Headroom | ~Price |
|---|---|---|---|---|
| AMD Instinct MI325X → | 256 GB | yes | ~180 GB | — |
| NVIDIA B200 → | 192 GB | yes | ~121.1 GB | — |
| AMD Instinct MI300X 192GB → | 192 GB | yes | ~121.1 GB | ~$15,000 |
| NVIDIA H200 → | 141 GB | yes | ~74.2 GB | — |
| Intel Gaudi 3 → | 128 GB | yes | ~62.3 GB | — |
| NVIDIA RTX PRO 6000 Blackwell → | 96 GB | yes | ~32.8 GB | ~$8,500 |
| NVIDIA H100 SXM5 80GB → | 80 GB | yes | ~18.1 GB | ~$30,000 |
| NVIDIA A100 SXM4 80GB → | 80 GB | yes | ~18.1 GB | ~$15,000 |
| NVIDIA H100 PCIe 80GB → | 80 GB | yes | ~18.1 GB | ~$25,000 |
| NVIDIA A100 PCIe 80GB → | 80 GB | yes | ~18.1 GB | ~$12,000 |
VRAM fit at FP16 (lower precision needs less). We don't estimate generation speed for image/video/audio — it depends on tool, resolution and steps.
FAQ
What Datacenter GPU hardware can run Wan 2.2 14B S2V?▶
On GenAIList, 10 Datacenter GPU GPUs have enough VRAM to hold Wan 2.2 14B S2V at FP16 — the most headroom is on the AMD Instinct MI325X (256 GB).
How fast is Wan 2.2 14B S2V on Datacenter GPU hardware?▶
We don't estimate generation speed for image/video/audio models — it depends on the tool, resolution and step count. This page ranks by which hardware fits the model in memory.