Revolutionizing Video Generation: 3 Groundbreaking AI Models You Need to Know
The AI Video Model Revolution: WAN 2.1, Hunyuan Image to Video, and LTXV
In the past two weeks, three groundbreaking AI video models—WAN 2.1, Hunyuan Image to Video, and LTXV—have been released, pushing the boundaries of video generation technology. Today, let's compare their key updates, usage tips, and hidden perks.
1. WAN 2.1: FP16 Breakthrough—Run Large Models with Limited VRAM
WAN 2.1 has made an unexpected breakthrough—its FP16 (16-bit floating point) inference outperforms BF16 (Brain Floating Point 16)! Previously, models running on BF16 produced lower-than-expected image quality. However, switching to FP16 significantly improves details and brings image quality close to full precision FP32 calculations.
For 1.3B (1.3 billion parameters) small models, the improvement is visibly noticeable.
For 14B (14 billion parameters) large models, dynamic rendering and detail refinement have reached a new level.
If you're still using the old BF16 version, it's time to upgrade!
For users with limited VRAM, WAN now provides an FP8_Scaled version. While slightly slower than regular FP8, it ensures high-quality outputs, making it a lifesaver for low-end GPUs.
Try the new workflow: WAN 2.1 Demo Page
💡 Tips:
New users: Start with the 1.3B model—it's lightweight and runs smoothly.
Power users: The 14B + FP16 combo is ideal for high-quality results. 16GB+ VRAM recommended.
2. Hunyuan Image to Video v2: More Accurate Image Guidance
Hunyuan Image to Video has fast update cycles. Just one day after release, the team launched v2 "fix version", and it’s not just a simple bug fix—it’s a refined architecture upgrade.
V2 vs. V1 Differences:
V2: Follows input images more accurately, making the generated video closer to the initial image.
V1: Offers smoother motion transitions, making it better suited for creative flexibility.
Official Demo Page: Hunyuan Video Demo
💡 Tips:
Use high-resolution images as input for better detail preservation.
Keep frame rate reasonable (24-30 FPS is enough) to avoid excessive VRAM consumption.
3. LTXV 0.9.5: The Lightweight "Speed Demon"
If WAN and Hunyuan are too slow for your workflow, LTXV 0.9.5 is your answer. This model is optimized for efficiency, running smoothly on an RTX 3060 for quick short video generation.
Ultra-lightweight architecture: Faster inference speeds.
Beginner-friendly: Minimal setup, simply input an image and adjust parameters—results in minutes.
Perfect for simple animations and looped videos.
Official Demo Page: LTXV Demo
Community feedback has been highly positive, especially for looping animations.
💡 Tips:
LTXV isn’t heavily dependent on input image quality—even rough sketches work well.
For sharper outputs, add an edge-enhancing pre-processing node.
4. Bonus: SaveWEBM Node Upgrade—Smoother Video Workflow
Apart from the model updates, SaveWEBM Node has received a major workflow enhancement:
Now supports in-node video preview
Can directly load WebM files for workflow reconstruction
Faster debugging and iteration
This means you can instantly review your generated videos without hunting for saved files, making the workflow much more efficient!
5. Summary—Which Model to Choose?
For best image quality → WAN 2.1
For better input-image accuracy → Hunyuan v2
For fastest generation speed → LTXV
Download the latest versions now and start creating! 🚀