# How to Generate a Short AI Video Locally (Wan 2.2)

> The honest local text-to-video path: Wan 2.2 TI2V-5B in ComfyUI — three model files, real VRAM numbers, and a five-second clip.

- Canonical: https://guides-ai.pages.dev/guides/generate-short-ai-video-locally/
- Plate 12.06 · Topic: AI images (https://guides-ai.pages.dev/topics/image/)
- Published: 06 Sept 2026 · 4 min read
- Source site: guides-ai — https://guides-ai.pages.dev/

Local text-to-video is real now, but only in a narrow band of hardware. This guide uses **Wan 2.2 TI2V-5B**, the hybrid text/image-to-video model that ComfyUI recommends for consumer cards.

## 1. The VRAM reality

Read this before downloading 20 GB.

| Hardware | What actually happens |
| --- | --- |
| 8 GB+ VRAM | Wan 2.2 **5B** works — ComfyUI's docs say it "should fit well on 8GB vram with the ComfyUI native offloading" |
| 12–16 GB | Same model, comfortably, with room for longer clips |
| 24 GB (4090) | Wan's own README: a 5-second 720P clip "in under 9 minutes on a single consumer-grade GPU" |
| Under 8 GB | Nothing worth your evening. Use a hosted service. |

The 14B Wan models are not a consumer option — the project documents them as needing on the order of 80 GB for single-GPU inference at standard settings. Offloading spills weights into system RAM, so RAM matters here almost as much as VRAM, and a slower card means minutes-per-second-of-video, not seconds.

## 2. Update ComfyUI

Video nodes move fast; a template that fails to load almost always means an old build. Use **Manager → Update All** in the ComfyUI interface, or, for a manual install:

```bash
git pull
pip install -r requirements.txt
```

Brings ComfyUI and its dependencies to the current version. The desktop app updates itself.

## 3. Download three files

From the `Comfy-Org/Wan_2.2_ComfyUI_Repackaged` repository on Hugging Face, into these exact folders:

```text
ComfyUI/models/diffusion_models/wan2.2_ti2v_5B_fp16.safetensors
ComfyUI/models/vae/wan2.2_vae.safetensors
ComfyUI/models/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors
```

Three separate folders — this is the step people get wrong. Wan is not a single checkpoint, so `models/checkpoints` stays empty here.

## 4. Open the template

In ComfyUI, open the **Template Library** and search for **Wan2.2 5B**. That loads the official workflow with the nodes already wired: the diffusion model loader, the UMT5 text encoder, the Wan VAE, a sampler, and a video output node.

Before running, click each loader node and confirm it points at the file you downloaded.

## 5. Render

Type your prompt into the positive prompt node, keep the template's resolution and frame count for the first run, then press `Ctrl + Enter`.

The finished clip lands in `ComfyUI/output`. Watch the terminal, not the browser: the first run also loads ~20 GB from disk, so the initial render is much slower than the second.

Short prompts describing one continuous shot work best — camera move, subject, setting. Ask for a cut or a scene change and you get mush.

---

Next: [set up ComfyUI properly first](/guides/comfyui-first-workflow/) or [upscale the frames afterwards](/guides/upscale-images-locally/).