Wan Video 2.1 14B
Frontierby Alibaba
State-of-the-art open-source video generation model from Alibaba. 14B parameter 3D DiT with exceptional motion quality, temporal coherence, and visual fidelity. Supports text-to-video and image-to-video.
- State-of-the-art open video generation
- 14B params for exceptional quality
- Text-to-video and image-to-video
- Apache 2.0 — fully open for commercial use
Your hardware
Detecting...
Image Quality Benchmarks
Measured quality metrics for Wan Video 2.1 14B outputs.
How often humans prefer this model's output (0-100%)
Visual quality and composition rating (5-9 scale)
VRAM by Scenario
VRAM estimates at FP16 and FP8 precision. FP8 uses ~40% less memory with minimal quality loss. Grade shows how well each GPU handles the generation workload.
FP16 (full precision)
| Scenario | VRAM | RTX 4090 24GB | RTX 3060 12GB | RTX 4060 8GB | MacBook Pro M4 Pro 24GB |
|---|---|---|---|---|---|
| 512×512 · 25 frames | 54.1 GB | F | F | F | F |
| 768×512 · 25 frames | 56.2 GB | F | F | F | F |
| 768×512 · 100 frames | 62.5 GB | F | F | F | F |
| 1280×720 · 25 frames | 64.6 GB | F | F | F | F |
FP8 (quantized — ~40% less VRAM)
| Scenario | VRAM | RTX 4090 24GB | RTX 3060 12GB | RTX 4060 8GB | MacBook Pro M4 Pro 24GB |
|---|---|---|---|---|---|
| 512×512 · 25 frames | 29.5 GB | D | F | F | F |
| 768×512 · 25 frames | 31.6 GB | D | F | F | F |
| 768×512 · 100 frames | 37.9 GB | F | F | F | F |
| 1280×720 · 25 frames | 40.1 GB | F | F | F | F |
Optimization Tips
Turbo / LCM distillation
Use distilled scheduler at 4-8 steps for faster iteration
Run with Python
from diffusers import WanPipeline
import torch
pipe = WanPipeline.from_pretrained(
"Wan-AI/Wan2.1-T2V-14B",
torch_dtype=torch.float16
)
pipe.to("cuda")
frames = pipe(
prompt="your prompt here",
num_inference_steps=50,
guidance_scale=5.0,
num_frames=81,
).frames[0]
# Save frames or export as videoGet started
Setup instructions for running Wan Video 2.1 14B locally
1. Download the model
Get the checkpoint from HuggingFace
2. Place in:
ComfyUI/models/checkpoints/3. Launch ComfyUI
python main.pyMemory Breakdown
VRAM allocation for 25 frames at 768×512 on RTX 4090 24GB
Estimated Generation Time
25 frames at 768×512, 30 steps, FP16.
Sample Outputs
Available Formats & Downloads
Download Wan Video 2.1 14B in different precisions. Lower precision = less VRAM but slight quality loss.
| Formato | Precisión | Tamaño | Proveedor | |
|---|---|---|---|---|
| safetensorsRecomendado | FP16 | 28.3 GB | official | Descargar |
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Frequently asked questions
FAQ — Wan Video 2.1 14B
How much VRAM does Wan Video 2.1 14B need for video?
Wan Video 2.1 14B (14B parameters) requires approximately 56.2 GB of VRAM at FP16 precision for generating 25 frames at 768×512. Video generation typically requires more VRAM than image generation due to temporal attention layers.
Can I run Wan Video 2.1 14B on RTX 4090?
Wan Video 2.1 14B exceeds the RTX 4090's 24 GB VRAM at FP16 for video generation. Consider reducing resolution, frame count, or using a GPU with more VRAM.
How long does it take to generate a video with Wan Video 2.1 14B?
On a reference GPU (RTX 4090 24GB), Wan Video 2.1 14B generates a 25-frame video at 768×512 in approximately ~3m 10s at FP16 with 30 inference steps. Faster GPUs with higher memory bandwidth will reduce generation time.
What resolution and frame count does Wan Video 2.1 14B support?
Wan Video 2.1 14B supports up to 1280×720 resolution and 81 frames per generation at 16 FPS. Higher resolutions and frame counts require proportionally more VRAM.
About Wan Video 2.1 14B
See also