--- title: "Run Wan video generation on a cloud GPU from $0.163/hr | PowerGPU" description: "Wan2GP on a fixed-price cloud GPU: one-click template, running in ~30 s, from $0.163/hr on RTX 4090. Best GPUs, volumes, per-second billing." url: https://powergpu.ai/templates/wan2gp last_modified: 2026-09-14T11:04:20+00:00 prices_as_of: 2026-09-14 site: PowerGPU (powergpu.ai) --- Template · Video generation · CUDA 12.9 # Run Wan video generation on a cloud GPU, in 30 seconds Run Wan and other video-generation models on modest VRAM, with a simple UI. Wan2GP ("Wan for the GPU poor") runs Wan 2.x, Hunyuan and other text- and image-to-video models with aggressive offloading and quantization, so 720p clips are possible on 16–24 GB cards. A simple web UI hides the memory tricks. From **$0.163** /hr on an interruptible RTX 4090. Wan2GP powergpu/wan2gp (CUDA 12.9) (SSH) (Jupyter) Pinned image, rebuilt on upstream releases. Override env, ports and disk at deploy. ### Running in ~30 s Pre-cached image, ports mapped, TLS terminated — the stack is working before you finish reading this. ### Template is free You pay the GPU price only: Wan2GP on a RTX 4090 is $0.327/hr on-demand, $0.163/hr interruptible, billed per second. ### Volumes for state Models, datasets and outputs live on a $0.08/GB/mo volume; the instance stays disposable. ### Private by default Dedicated GPU, encrypted disk, crypto payments, no KYC, no stored IPs — Jupyter and SSH behind your own credentials. ## Best GPUs for Wan2GP Three price points that run this template well — Good, Better, Best. Every model in the catalogue works; these are the value picks. | Tier | GPU | VRAM | On-demand | Interruptible | Why this card | | | --- | --- | --- | --- | --- | --- | --- | | (Good) | [RTX 4090](https://powergpu.ai/gpu/rtx-4090) | 24 GB | $0.327 | $0.163 | 24 GB: Wan 2.1 14B at 480p–720p with offloading. | [Deploy](https://cloud.powergpu.ai/?gpu=rtx-4090) | | (Better) | [RTX 5090](https://powergpu.ai/gpu/rtx-5090) | 32 GB | $0.439 | $0.219 | 32 GB GDDR7 — noticeably faster clips and fewer offload stalls. | [Deploy](https://cloud.powergpu.ai/?gpu=rtx-5090) | | (Best) | [H100 PCIE](https://powergpu.ai/gpu/h100-pcie) | 80 GB | $1.867 | $0.933 | 80 GB for full-precision video models without offloading. | [Deploy](https://cloud.powergpu.ai/?gpu=h100-pcie) | Need more VRAM? The [full catalogue](https://powergpu.ai/gpus) lists all 80 models with live availability; the [VRAM guide](https://powergpu.ai/guides/llm-vram-requirements) sizes models to cards. ## Deploy Wan2GP from the console, CLI or API Pick the template in the [console](https://cloud.powergpu.ai/) deploy bar, or script it: - **Console** — filter by GPU, choose *Wan2GP* in the template picker, set disk and env, deploy. - **CLI** — pip install powergpu, then the command on the right. [CLI reference](https://powergpu.ai/cli). - **API** — POST /v1/instances with "template": "wan2gp". [REST reference](https://powergpu.ai/api). - **Own image** — any OCI reference works too; we inject the NVIDIA runtime. [Template docs](https://powergpu.ai/docs/templates). *deploy — wan2gp* ``` $ powergpu launch --gpu rtx-4090 --template wan2gp \ --disk 100 --volume models:/workspace/models ✓ instance i-7a41c0e2 running (27.9s) # Wan2GP · RTX 4090 · $0.327/hr · per second # https://i-7a41c0e2.powergpu.ai:8888 (TLS) $ powergpu stop i-7a41c0e2 # billing ends this second ``` ## What is inside the Wan2GP template - **Image**: powergpu/wan2gp - **CUDA**: CUDA 12.9 - **Access**: SSH shell · JupyterLab on a mapped port - **Category**: [Video generation](https://powergpu.ai/templates#video) - **Storage**: Instance NVMe disk (sized at deploy) + optional [network volumes](https://powergpu.ai/products/volumes) - **Billing**: GPU price only, per second — no template fee, no setup fee ## Other video generation templates - [Open-Sora on a cloud GPU](https://powergpu.ai/templates/open-sora) — The open text-to-video model, ready to generate and fine-tune. - [All 37 templates](https://powergpu.ai/templates) ## Wan2GP on a cloud GPU: FAQ Environment variables, ports and custom images are covered in the [template docs](https://powergpu.ai/docs/templates). **How much does it cost to run Wan2GP on a cloud GPU?** Only the GPU price — the template is free. From $0.163/hr on an interruptible RTX 4090, $0.327/hr on-demand on a RTX 4090. Billing is per second, so an hour of tinkering costs an hour, not a day. Storage is $0.08/GB/month. **How long does Wan2GP take to start?** About 30 seconds from the deploy click: the image is pre-cached on hosts, ports are mapped and TLS is terminated for you. Restarting a stopped instance is faster, and your disk is exactly as you left it. **Can I keep my models and outputs between sessions?** Yes — attach a volume at deploy. Everything on the volume survives instance destruction and mounts on the next instance in the region in seconds, at $0.08/GB/month. The instance disk itself survives stop/start but not destroy. **How long does a 5-second clip take?** Roughly 8–15 minutes at 720p on an RTX 4090 with offloading, 4–8 minutes on an 80 GB H100 without it. Batch overnight on interruptible pricing to halve the cost per clip. --- *About PowerGPU:* PowerGPU (powergpu.ai) is a cloud GPU rental service offering 80 NVIDIA GPU models — from the RTX A2000 at $0.024/hr to the B300 — at fixed prices set at least 30% below the public GPU marketplace median and re-checked weekly (H100 SXM: $1.428/hr on-demand). Billing is per second with no minimums; payment is crypto only (USDT, BTC, XMR, ETH, SOL, LTC, TRX) with no KYC. Instances run in Tier-III datacenters across 32 regions with a 99.9% uptime SLA and deploy in about 30 seconds from the web console (cloud.powergpu.ai) or the REST API. Source: https://powergpu.ai/templates/wan2gp · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt