How to Generate AI Videos Locally
Local AI video generation crossed the usability threshold in 2025. Models like Wan 2.1 and HunyuanVideo can produce coherent video clips on consumer hardware, and you do not need a cloud subscription or API key to use them. This guide covers the complete setup: hardware requirements, model selection, installation, and practical tips for getting good results.
The Current State of Local Video Generation
AI video generation is roughly where image generation was two years ago. The outputs are impressive but not perfect. You will see occasional artifacts, limb distortions, and temporal inconsistencies. That said, the quality has improved dramatically. Short clips (2-5 seconds) at 480p-720p are now reliably coherent, and the models keep getting better.
Two model families dominate local video generation in 2026:
- Wan 2.1 by Alibaba -- Available in 1.3B and 14B parameter sizes. The most accessible option for consumer GPUs.
- HunyuanVideo 1.5 by Tencent -- The quality leader. Produces more cinematic results but requires more VRAM and generation time.
Hardware Requirements
Video generation is the most demanding local AI task. It requires significantly more VRAM and time than image generation because the model must produce multiple coherent frames.
| Model | Min VRAM | Recommended VRAM | Time per Clip |
|---|---|---|---|
| Wan 2.1 1.3B | 8 GB | 10 GB | 30-60 seconds |
| Wan 2.1 14B FP8 | 14 GB | 16 GB | 2-5 minutes |
| HunyuanVideo 1.5 FP8 | 14 GB | 16 GB | 3-8 minutes |
System RAM matters too. Budget at least 32 GB of system RAM for video generation. The models need working memory beyond what sits on the GPU, and running out of RAM will either crash the process or force slow disk swapping.
Storage: Wan 2.1 14B requires approximately 15 GB of model files. HunyuanVideo requires roughly 20 GB. Plan for 40+ GB of free disk space to accommodate models and generated output.
Wan 2.1 1.3B vs 14B vs HunyuanVideo
| Feature | Wan 1.3B | Wan 14B FP8 | HunyuanVideo FP8 |
|---|---|---|---|
| Output Resolution | 480p | 720p | 720p |
| Motion Coherence | Good | Very Good | Excellent |
| Prompt Following | Basic | Good | Very Good |
| Camera Motion | Limited | Moderate | Strong |
| VRAM Required | 8 GB | 16 GB | 16 GB |
| Speed | Fast | Moderate | Slow |
| Model Files | 3 files | 3 files | 4 files |
Which Model Should You Start With?
If you have 8-10 GB VRAM, Wan 2.1 1.3B is your only option and it is a good one. Quick generation times let you iterate on prompts rapidly. If you have 16+ GB VRAM, start with Wan 2.1 14B for the best balance of quality and speed, then try HunyuanVideo when you want maximum quality and are willing to wait longer.
Step 1: Set Up the Backend
All three video models run through ComfyUI, which handles the actual inference. Locally Uncensored provides the frontend and automates workflow construction so you never need to touch ComfyUI's node editor.
git clone https://github.com/PurpleDoubleD/locally-uncensored.git
cd locally-uncensored
npm install
npm run devThe app auto-detects ComfyUI on your system. If ComfyUI is not installed, download the portable release from the ComfyUI GitHub page. Locally Uncensored scans common installation paths automatically, or you can set the path manually in Settings.
Step 2: Download Video Models
Open the Model Manager tab in Locally Uncensored. Under the Video section, you will find pre-configured bundles for all three models. Click Install All on your chosen bundle.
Each bundle downloads the correct set of files:
Wan 2.1 (1.3B or 14B) -- 3 files
- Model weights -- The core video generation model
- VAE -- Video encoder/decoder for frame reconstruction
- UMT5 -- Text encoder for prompt understanding
HunyuanVideo 1.5 -- 4 files
- Model weights -- The core video generation model
- VAE -- HunyuanVideo-specific VAE (not interchangeable with Wan)
- Qwen2.5 -- Primary text encoder
- CLIP_L -- Secondary text encoder
The distinction matters: Wan and HunyuanVideo use completely different VAE and text encoder architectures. They cannot share these components. Locally Uncensored handles matching automatically -- it identifies the model type and loads the correct supporting files.
Step 3: Generate Your First Video
Switch to the Create tab. Select your video model from the model dropdown. Write a prompt describing the scene you want, then click Generate.
Behind the scenes, the app:
- Classifies the selected model (Wan vs HunyuanVideo)
- Locates the matching VAE and text encoders
- Builds the appropriate ComfyUI workflow
- Submits the workflow and polls until the video is complete
- Displays the result in the gallery with generation time
For your first generation, keep the prompt simple. Something like "a cat walking through a garden, sunny day, gentle breeze" will test whether the pipeline works before you invest time in complex prompts.
Prompt Tips for Video Generation
Video prompts work differently than image prompts. You need to describe motion, not just a static scene.
Describe the Action
Be explicit about what moves and how. "A woman walks toward the camera" is better than "a woman standing outside." The model needs motion cues to generate coherent temporal sequences.
Specify Camera Behavior
Camera descriptions help significantly, especially with HunyuanVideo: "slow pan left across a mountain range," "tracking shot following a car on a highway," or "static wide shot of a cityscape at sunset."
Keep It Short and Clear
Unlike image generation where long descriptive prompts can help, video models perform better with concise, focused descriptions. One clear action in one clear setting produces more coherent results than a paragraph of details.
Example Prompts
A golden retriever running through shallow ocean waves at sunset, slow motion, cinematic
Aerial drone shot slowly descending over a dense forest, morning fog between the trees
Close-up of coffee being poured into a white ceramic cup, steam rising, soft lightingTroubleshooting VRAM Issues
CUDA Out of Memory
Video generation consumes VRAM in bursts. If you are near the limit, reduce the output resolution or frame count. Close all other GPU applications including browser hardware acceleration (disable it in browser settings). For Wan 14B, ensure you are using the FP8 quantized version, not the full precision weights.
Generation Takes Extremely Long
Verify that ComfyUI is using your GPU and not falling back to CPU. Check the ComfyUI terminal output at startup -- it should list your CUDA device. CPU-based video generation is not practical; a single clip could take hours.
Output Has Artifacts or Flickering
This is common with the 1.3B model and shorter frame counts. Increasing the step count (try 30-40 for Wan) improves temporal coherence at the cost of speed. If artifacts persist, the prompt may be too complex for the model's capacity -- simplify it.
Wrong VAE or Text Encoder Error
This occurs when the app cannot find the matching support files for your video model. Open the Model Manager and verify all files in the bundle are downloaded. Wan requires UMT5; HunyuanVideo requires Qwen2.5. They are not interchangeable.
What to Expect Going Forward
Local video generation is improving rapidly. New models are released every few months with better motion coherence, longer clip durations, and lower VRAM requirements. The workflow in Locally Uncensored remains the same regardless of which model you use -- select, prompt, generate. As new video models become available, they will be integrated through the same ComfyUI backend and dynamic workflow builder.
If you are new to local AI entirely, start with our ComfyUI beginners guide to understand the foundation, then come back here once you are comfortable with image generation.