Wan2.1 FusionX 14B: Consistent Fast VideoGen with Low VRAM

Creating cinematic, detailed, and dynamic text to video content usually requires big models that are slow and extremely resource-heavy. We tried and even commercial grade models often struggle to strike a balance between motion realism, visual fidelity, and practical speed especially for hobbyists or researchers using consumer GPUs.

That's exactly where Wan2.1 14B FusionX (by Vrgamedevgirl84) comes that's fine-tuned on Wan 2.1 14B architecture and merged with video-gen diffusion models like CausVid, AccVideo, and MoviiGen1.1. It promises cinematic motion, rich detail, and practical runtimes. Even at as few as 6 to 8 steps, you will see smooth scene consistency, better lighting, and superior motion all optimized for ComfyUI.

By fusing these components, FusionX brings an open, cinematic-grade model to your local workflow. Whether you run FusionX standalone or as a LoRA on top of Wan 2.1 14B, you can get the visual richness or drop the step count without losing scene flow perfect for iterative setups.

If you want to explore cinematic text to video without relying on closed source solutions, Wan2.1 14B FusionX is one of the most practical options. It respects the licensing terms (mostly CC BY NC SA 4.0 for research and personal use) and is tuned for realistic output and great iteration speed.

Installation

1. New user need to install ComfyUI. Update ComfyUI from Manager tab if you already a Comfy user.

2. Install and (Native/Kijai) setup Wan 2.1 already explained in our
Step by Step tutorial. The native support will have little slow generation.

3. Download and setup Wan2.1 Fusion 14b Models. There two FusionX model variants you can choose from.

Type A: Basic (for Mid range VRAM)

(a) Download Wan2.1 Fusion 14b TxtToVideo / ImageToVideo Model from Hugging face and save it into your "ComfyUI/diffusion_models" folder.

(b) Rest of the models (VAE, Text encoders) already included in Wan2.1 setup.

Type B: GGUF support (for Mid and Low VRAM)

(a) First, setup Wan 2.1 GGUF.by City 96 already explained in our Wan installation tutorial. If you already done then its not required.

(b) Download GGUF Wan2.1 Fusion 14b TxtToVideo Model or GGUF Wan2.1 Fusion 14b ImgToVideo model available in Q2 (for Low quality with fast generation) to Q8(for best quality with high VRAM) variant from Hugging face repository. Save it into your "ComfyUI/models/unet" folder.

(c) Rest of the models (VAE, Text encoders) already included in GGUF setup so these are not required. But if you want then download and save it:

Text Encoder (umt5-xxl-encoder)- and save it into "ComfyUI/models/text_encoders" folder.

VAE - ( Wan2_1_VAE_bf16 ) and save it to "ComfyUI/models/vae" folder.

4. Restart you ComfyUI and refresh it.