Wan2.1 T2V 14B
Q4 GGUF download: city96/Wan2.1-T2V-14B-gguf - 10.12 GB on disk, read 2026-09-27. VRAM figures above are estimates; this is the actual file size.
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
vllm serve Wan-AI/Wan2.1-T2V-14BNew to this? Start with Ollama · serve to many users with vLLM.
Deep dive
Notes, sources, and the full write-up
Wan2.1 T2V 14B
Wan2.1 is an open and advanced video foundation model by Wan-AI (Alibaba). The T2V-14B variant generates high-quality 720P videos from text descriptions. It consistently outperforms both open-source and commercial solutions across multiple benchmarks.
Key features
- 720P video generation - high-quality 480P and 720P output
- 14B parameters - diffusion transformer with Flow Matching
- Apache 2.0 - fully open license
- Multilingual text - Chinese and English text generation in video
- Multiple tasks - T2V, I2V, video editing, T2I, video-to-audio
- Consumer GPU support - RTX 4090 compatible with optimizations
Performance
| GPU | Resolution | Time | Peak VRAM |
|---|---|---|---|
| RTX 4090 | 480P (832×480) | ~4 min | 8.19 GB (1.3B) |
| RTX 4090 | 720P (1280×720) | - | Offloaded |
| 8× GPU | 720P | Fast | FSDP |
How to run
# Clone repo
git clone https://github.com/Wan-Video/Wan2.1.git
cd Wan2.1
# Install
pip install -r requirements.txt
# Download model
huggingface-cli download Wan-AI/Wan2.1-T2V-14B --local-dir ./Wan2.1-T2V-14B
# Generate
python generate.py --task t2v-14B --size 1280*720 \
--ckpt_dir ./Wan2.1-T2V-14B \
--prompt "Your video description here"From the community
What users are saying
“Hey man... or woman, umm well that depends how you want to go about it. I think the easiest way which doesn't involve any terminals and code would be to download an application called ComfyUI Desktop.”
“With 4 x A6000 cards, I used '''torchrun --nprocpernode=8 generate.py --task t2v-14B --size 1280720 --ckptdir ./Wan2.1-T2V-14B --ditfsdp --t5fsdp --ulyssessize 8 --prompt "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage."''' to generate videos.”
“New here to Gitbub and have no idea how to download this program Can someone please give a easy to follow, step by step break down of how to download Wan2.1-I2v-14B-720P”
Frequently asked
Quick answers to common questions
How much VRAM does Wan2.1 T2V 14B need?
Wan2.1 T2V 14B with 14B parameters needs significant VRAM depending on quantization. Use our VRAM calculator for an exact estimate.
Is Wan2.1 T2V 14B better than other Wan models?
Wan2.1 T2V 14B has 14B parameters with 8,192 context - a strong choice for text-to-video, video-generation.
What license is Wan2.1 T2V 14B under?
Wan2.1 T2V 14B is released under the Apache 2.0 license, making it suitable for most commercial and personal projects.
What hardware runs Wan2.1 T2V 14B well?
With 14B parameters, Wan2.1 T2V 14B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Wan2.1 T2V 14B?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Step up to Q5_K_M or Q8_0 only if you have spare VRAM. Use our VRAM calculator to compare.
What models compete with Wan2.1 T2V 14B?
Wan2.1 T2V 14B competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Compare & pair with
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