tags:
- text-to-video
- diffusion
- merged-model
- video-generation
- wan2.1
widget:
- text: >-
Prompt: A gritty close-up of an elven princess kneeling in a rocky ravine,
calming a wounded, desert dragon. Its scales are cracked, dry, She wears a
crimson sash over bone-colored armor, her auburn hair half-tied back. The
camera dollies in rapidly as she reaches for its eye ridge. Lighting comes
from golden sunlight reflecting off surrounding rock, casting a warm,
earthy hue with no artificial glow.
output:
url: videos/Video_00063.mp4
- text: >-
Prompt: Tight close-up of her smiling lips and sparkling eyes, catching
golden hour sunlight. She wears a white sundress with floral prints and a
wide-brimmed straw hat. Camera pulls back in a dolly motion, revealing her
twirling under a cherry blossom tree. Petals flutter in the air, casting
playful shadows. Soft lens flares enhance the euphoric, dreamlike vibe.
(Before vs After — Left: Wan2.1 | Right: Merged model
Wan14BT2V_MasterModel)
output:
url: videos/AnimateDiff_00001.mp4
- text: >-
Prompt: A gritty close-up of a dwarven beastmaster’s face, his grey beard
braided tightly, brows furrowed as he looks just off-camera. The camera
dollies out over his shoulder, revealing a perched gryphon watching him
from a boulder, its feathers rustling slightly in the breeze. The moment
holds stillness and mutual trust. Lighting is early daylight, clean and
sharp with strong environmental clarity.
output:
url: videos/FusionX_00012.mp4
- text: >-
Prompt: A gritty close-up of a jungle tracker crouching low, face flushed
with focus as she watches a perched macaw a few feet ahead. Her cheek
twitches as she shifts forward, beads of sweat visible on her brow. The
camera slowly dollies in from below her line of sight, capturing the
moment her eyes widen in fascination. Lighting is rich and directional
from above, creating a warm glow over her face with minimal shadows.
output:
url: videos/FusionX_00005.mp4
- text: >-
Prompt: A gritty close-up of a battle-worn ranger kneeling in a scorched
clearing, calming a wounded gryphon whose wing is torn and bloodied. Its
feathers are dusky bronze with streaks of ash-gray. She wears soot-covered
hunter green armor, her blonde hair pulled into a loose braid. The camera
dollies in as her hand brushes the creature's sharp beak. Lighting comes
from late afternoon sun filtering through smoke, casting a burnt-orange
haze across the frame.
output:
url: videos/Video_00069.mp4
base_model:
- Wan-AI/Wan2.1-T2V-14B
license: apache-2.0
🌀 Wan2.1_14B_FusionX
High-Performance Merged Text-to-Video Model
Built on WAN 2.1 and fused with research-grade components for cinematic motion, detail, and speed — optimized for ComfyUI and rapid iteration in as few as 6 steps.
Merged models for faster, richer motion & detail — high performance even at just 8 steps.
📌 Important: To match the quality shown here, use the linked workflows or make sure to follow the recommended settings outlined below.
🌀 Preview Gallery
These are compressed GIF previews for quick viewing — final video outputs are higher quality.
📂 Workflows & Model Downloads
💡 ComfyUI workflows can be found here:
👉 Workflow Collection (WIP)📦 Model files (T2V, I2V, Phantom, VACE):
👉 Main Hugging Face Repo
🧠 GGUF Variants:
- 🖼️ FusionX Image-to-Video (GGUF)
- 🎥 FusionX Text-to-Video (GGUF)
- 🎞️ FusionX T2V VACE (for native)
- 👻 FusionX Phantom
🎬 Example Videos
Want to see what FusionX can do? Check out these real outputs generated using the latest workflows and settings:
Text-to-Video
👉 Watch ExamplesImage-to-Video
👉 Watch ExamplesPhantom Mode
👉 Watch ExamplesVACE Integration
👉 Watch Examples
🚀 Overview
A powerful text-to-video model built on top of WAN 2.1 14B, merged with several research-grade models to boost:
- Motion quality
- Scene consistency
- Visual detail
Comparable with closed-source solutions, but open and optimized for ComfyUI workflows.
💡 Inside the Fusion
This model includes the following merged components:
- CausVid – Causal motion modeling for better flow and dynamics
- AccVideo – Better temporal alignment and speed boost
- MoviiGen1.1 – Cinematic smoothness and lighting
- MPS Reward LoRA – Tuned for motion and detail
- Custom LoRAs – For texture, clarity, and facial enhancements
All merged models use permissive open licenses (Apache 2.0 / MIT).
🔧 Usage Details
Text-to-Video
- CGF: Must be set to
1 - Shift:
1024x576: Start at11080x720: Start at2- For realism → lower values
- For stylized → test
3–9
- Scheduler:
- Recommended:
uni_pc - Alternative:
flowmatch_causvid(better for some details)
- Recommended:
Image-to-Video
- CGF:
1 - Shift:
2works best in most cases - Scheduler:
- Recommended:
dmp++_sde/beta
- Recommended:
- To boost motion and reduce slow-mo effect:
- Frame count:
121 - FPS:
24
- Frame count:
🛠 Technical Notes
- Works in as few as 6 steps
- Best quality at 8–10 steps
- Drop-in replacement for
Wan2.1-T2V-14B - Up to 50% faster rendering, especially with SageAttn
- Works natively and with Kaji Wan Wrapper
Wrapper GitHub - Do not re-add merged LoRAs (CausVid, AccVideo, MPS)
- Feel free to add other LoRAs for style/variation
- Native WAN workflows also supported (slightly slower)
🧪 Performance Tips
- RTX 5090 → ~138 sec/video at 1024x576 / 81 frames
- If VRAM is limited:
- Enable block swapping
- Start with
5blocks and adjust as needed
- Use SageAttn for ~30% speedup (wrapper only)
- Do not use
teacache - "Enhance a video" (tested): Adds vibrance (try values 2–4)
- "SLG" not tested — feel free to explore
🧠 Prompt Help
Want better cinematic prompts? Try the WAN Cinematic Video Prompt Generator GPT — it adds visual richness and makes a big difference in quality. Download Here
📣 Join The Community
We’re building a friendly space to chat, share outputs, and get help.
- Motion LoRAs coming soon
- Tips, updates, and support from other users
⚖️ License
Merged under permissive licenses:
- Apache 2.0 / MIT
- You can use, modify, and redistribute
- You must retain original license info
- Outputs are not necessarily licensed — do your due diligence
This model is for research, education, and personal use only. Commercial use is your own responsibility. Please consult a legal advisor before monetizing outputs.
🙏 Credits
- WAN Team (base model)
- aejion (AccVideo)
- Tianwei Yin (CausVid)
- ZuluVision (MoviiGen)
- Alibaba PAI (MPS LoRA)
- Kijai (ComfyUI Wrapper)
And thanks to the open-source community!











