By GraphicCardPrices. Requirements checked against the official Wan 2.2 documentation on .
This guide is for creators who want to make short AI video clips on their own computer instead of paying a monthly subscription, and who are deciding whether their current graphics card is enough.
Wan 2.2 is Alibaba's open video model family. It turns a text prompt, or a still image plus a prompt, into a video clip. The small TI2V-5B model handles both jobs at 720P and 24 frames per second; the larger A14B models give higher quality but need far more memory.
License note: the README says the models are licensed under Apache 2.0, which permits commercial use. You remain responsible for what you generate and share.
What GPU do you need?
The official README says: "This command can run on a GPU with at least 24GB VRAM (e.g, RTX 4090 GPU)." (source)
| Tier | VRAM | What it runs | Example cards |
|---|---|---|---|
| Minimum | 8 GB | TI2V-5B in ComfyUI. ComfyUI's docs say it "should fit well on 8GB vram with the ComfyUI native offloading." source | RTX 4060, RTX 5060, RTX 3060 (12GB version) |
| Comfortable | 24 GB | The official TI2V-5B script at 720P. The README table shows a 22.9 GB peak on one RTX 4090. source | RTX 3090, RTX 4090 |
| Best | 32 GB | The most headroom for TI2V-5B on a consumer card. Still below the 41.3 GB peak the README table shows for the A14B models at 480P on one GPU. source | RTX 5090 |
Lowest recorded prices by tier
The cheapest New and Used listings we have recorded for each tier, among NVIDIA GeForce RTX cards with at least that much VRAM. Used includes renewed and refurbished cards. Each is a recorded Amazon US price, not a live checkout price; the model page shows every listing and its condition.
| Tier | Lowest New | Lowest Used |
|---|---|---|
| Minimum (8GB+) | $419.99 RTX 5050 8GB Recorded 2026-10-24 11:09:56 UTC | $249.97 RTX 2060 SUPER 8GB Recorded 2026-09-30 05:03:30 UTC |
| Comfortable (24GB+) | $4,490.00 RTX 4090 24GB Recorded 2026-10-26 22:50:21 UTC | $1,699.99 RTX 3090 24GB Recorded 2026-09-29 16:27:49 UTC |
| Best (32GB+) | $7,199.99 RTX 5090 32GB Recorded 2026-10-16 21:16:50 UTC | No Used listing recorded |
How to get started
- Easiest route: install ComfyUI (a desktop app is available for Windows and macOS), then open the Wan 2.2 template from the official ComfyUI Wan 2.2 tutorial. It lists the exact model files and the folders they go in.
- Start with the TI2V-5B workflow. The tutorial notes that the default video size is kept small for low-VRAM users; raise it only once a short clip works.
- Command-line route: clone the Wan 2.2 repository, install its requirements (PyTorch 2.4.0 or newer), download the weights from Hugging Face or ModelScope, and run
generate.py. If you run out of memory, the README suggests the--offload_model True,--convert_model_dtypeand--t5_cpuoptions.
Full instructions are in the official Wan 2.2 repository.
Things to check before you buy
NVIDIA, AMD and Intel
The Wan 2.2 README's commands and timing table only cover NVIDIA GPUs. ComfyUI's README says its manual install "Supports all operating systems and GPU types (NVIDIA, AMD, Intel, Apple Silicon, Ascend)", but neither project publishes Wan 2.2 memory figures for AMD or Intel cards. The price table above covers NVIDIA GeForce RTX cards.
System RAM
Offloading keeps parts of the model in system memory instead of VRAM, so an 8GB card leans on your RAM. Neither README gives a RAM figure; the ComfyUI README's general claim is that it can run big models on "as low as 4GB vram + 8GB ram relatively quickly".
Speed
The README's own table shows TI2V-5B taking 534.7 seconds for a 720P text-to-video clip on one RTX 4090, about nine minutes. Offloading on smaller cards adds time. We have not run our own benchmarks.
Older 8GB option
The Wan 2.1 README states: "The T2V-1.3B model requires only 8.19 GB VRAM." That is slightly more than an 8GB card has, so expect to rely on its offload options.
Wan 2.2 questions
How much VRAM does Wan 2.2 need?
The official README says the TI2V-5B command can run on a GPU with at least 24GB of VRAM, such as an RTX 4090, and its table shows a 22.9 GB peak at 720P. With the offload options, the A14B models peaked at 41.3 GB at 480P on one GPU, more than any consumer card in our catalog.
Can I run Wan 2.2 on an 8GB graphics card?
ComfyUI's official Wan 2.2 tutorial says the 5B version should fit well on 8GB of VRAM with ComfyUI native offloading. Expect longer render times than on a 24GB card, because parts of the model are kept in system RAM.
Can I use Wan 2.2 videos commercially?
The Wan 2.2 README says the models are licensed under Apache 2.0, which allows commercial use. You are still responsible for the content you generate, including any people, brands or music in it.
Compare cards
Estimate memory for language models with the LLM VRAM estimator, see typical prices per memory size in GPU prices by VRAM, or compare pairs: RTX 3060 vs RTX 4060, RTX 3090 vs RTX 4090, RTX 5060 Ti vs RTX 4060 Ti. More local AI GPU guides.
Sources
- Wan 2.2 README (24GB and 80GB notes, efficiency table, license), checked
- ComfyUI Wan 2.2 tutorial (8GB note for TI2V-5B), checked
- ComfyUI README (GPU support), checked
- Wan 2.1 README (8.19 GB figure), checked
We have not benchmarked these tools. Requirements change between releases, so check the repository before you buy.