Wan 2.2 vs HunyuanVideo: Which Generates Better Video in ComfyUI

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If you work with ComfyUI and need to generate professional-quality AI video, you’ve probably run into the eternal question: Wan 2.2 or HunyuanVideo. Both models dominate video generation in ComfyUI, but each has strengths and limitations that directly impact your workflow and final results. The official weights and code are published by Wan-Video on GitHub and by Tencent in the HunyuanVideo repository respectively.

The Wan vs HunyuanVideo comparison isn’t simple: it depends on your hardware, your deadlines, and what kind of motion your projects need. In this guide I’ll break down the technical, performance, and practical differences so you can make the right call.

If you also want to see both models tested alongside LTXV-2.3, SCAIL-2, and Wan 2.1 on the same RTX 3090, check our real 5-test local AI video comparison.

At a Glance: Quick Comparison

VRAM Consumption: The Limiting Factor

Memory consumption is the first factor that decides whether a model is viable for your setup. Wan 2.2 or HunyuanVideo have very different profiles:

Wan 2.2 offers two versions with radically different requirements:

• Wan 2.2 1.3B: needs 12GB of VRAM with no offload. It’s the most accessible option if you have a mid-to-high-end GPU.
• Wan 2.2 14B: needs 24GB with no offload, though with sequential_cpu_offload enabled you can bring that down to 14GB. Your SSD speed matters here.

HunyuanVideo: needs 24GB with no offload, but with enable_sequential_cpu_offload it drops to 16GB. It’s more efficient than Wan 14B in offload mode, using roughly 2GB less peak memory.

⚠️ Important: If your GPU has less than 16GB, Wan 1.3B is your only realistic option between these two models. With 24GB, both run without performance compromises.

👉 Quick takeaway: Available VRAM is your first filter. With 12GB you only get Wan 1.3B; with 16GB+ you can access Wan 14B or HunyuanVideo with offload.

Render Speed: The Time Factor

For a 33-frame video (roughly 1.3 seconds at 25fps), on an RTX 3090 with no offload:

• Wan 1.3B: 8-12 minutes
• Wan 14B: 12-18 minutes
• HunyuanVideo: 18-25 minutes

HunyuanVideo is slower, but that gap is justified if the quality makes up for it. Wan 1.3B is the fastest option, ideal if you need to iterate through multiple versions quickly.

With sequential_cpu_offload enabled, times increase roughly 30-40%, but VRAM usage drops significantly. Many professional users accept that trade-off to use 16GB GPUs.

💡 Tip: If you’re working through multiple iterations, calculate the total time. Wan 1.3B can generate 4 versions while HunyuanVideo finishes 1. Sometimes speed outweighs the marginal quality gain.

👉 Quick takeaway: If time is critical, Wan 14B with offload offers the best balance. HunyuanVideo is slower but generates superior motion.

Motion Quality: The Real Differentiator

This is where the Wan 2.2 or HunyuanVideo ComfyUI comparison gets interesting. HunyuanVideo produces noticeably smoother and more natural motion, especially for complex human actions: people walking, gestures, facial expression changes.

Wan 2.2 14B comes close to HunyuanVideo in quality, with subtle differences that only show up under detailed analysis. For many professional projects, the difference is imperceptible to an untrained eye.

Wan 1.3B, on the other hand, shows clear limitations in complex motion. Characters tend to look stiff, gestures are less natural, and there’s more “jitter” in transitions. It’s acceptable for simple scenes (static objects, slow camera moves, abstract effects), but insufficient for character animation.

Prompt Understanding: Instructions and Control

HunyuanVideo includes a natural-language LLaVA encoder, which means it understands more complex, contextual instructions. You can write long prompts with multiple conditions and the model will correctly interpret the nuance.

Wan 2.2 works best with short, direct prompts in English. If you write complex instructions, it tends to ignore secondary details. That’s not a flaw, it’s simply a model characteristic: it requires you to be concise and specific.

Practical example:

• HunyuanVideo understands: “A woman walking through a foggy forest at sunrise, with soft light filtering through the trees, looking thoughtful”
• Wan 2.2 prefers: “Woman walking in misty forest, sunrise, soft light”

📌 Keep in mind: This factor matters if you work with clients who provide detailed briefs, or if you need maximum creative control over the final output.

T2V vs I2V Models: Node Structure in ComfyUI

Both Wan and HunyuanVideo have separate models for:

• T2V (text-to-video): generate video from a text description
• I2V (image-to-video): generate video by animating a still image

The nodes in ComfyUI are specific to each function. You can’t use the T2V model for I2V or vice versa. Make sure you load the right one for your workflow. This matters especially if you’re building reusable workflows.

The Third Option: LTX Video

Before deciding between Wan and HunyuanVideo, consider LTX Video if your priority is extreme speed:

• Generates 30-90 seconds of video in 30-90 seconds (not an exaggeration)
• Only needs 8GB VRAM
• Lower visual quality than Wan 14B and HunyuanVideo, but functional
• Ideal for prototypes, quick tests, and budget-constrained projects

Many professional users use LTX to iterate and experiment, then generate the final version with Wan 14B or HunyuanVideo when quality is critical.

Practical Recommendation Based on Your Hardware

If you have 12GB VRAM: Wan 1.3B is your only realistic option. You’ll accept that complex motion won’t be perfect, but the speed and footprint make up for it.

If you have 16-24GB VRAM and value speed: Wan 14B with offload. You’ll get 95% of HunyuanVideo’s quality in 70% of the time.

If you have 16-24GB VRAM and quality is your priority: HunyuanVideo. The smooth motion of characters and complex actions justifies the wait.

If you have 24GB+ VRAM: Try both on your specific project. Each has different nuances. Some users generate versions in parallel and pick the best one.

Specific Use Cases

• Character animation (dance, acting): HunyuanVideo wins. Natural motion is critical.
• Visual effects and transitions: Wan 14B is enough and faster.
• Corporate and explainer videos: Wan 1.3B holds up if the motion is simple.
• Fast iteration and prototyping: LTX Video, no question.
• Product rotation videos: Wan 1.3B or 14B both work well.

👉 Quick takeaway: Choose based on content type. Complex characters → HunyuanVideo. Simple content or prototyping → Wan 1.3B or LTX.

FAQ

Q: Is HunyuanVideo really better than Wan 2.2?

A: For complex human actions (walking, dancing, gestures): HunyuanVideo has smoother motion. For simple scenes (landscapes, camera movement, floating objects): the difference is small. Wan 2.2 14B is very competitive and more VRAM-accessible with offload.

Q: Which one has more community support and custom nodes?

A: Wan 2.2 has a more mature node ecosystem in ComfyUI. HunyuanVideo is growing fast but has fewer shared workflows. For resources, tutorials and examples, Wan 2.2 has more content available.

Q: Can I use the same workflow for Wan and HunyuanVideo?

A: No. The nodes are different and model-specific. Wan uses WanVideoModelLoader, WanVideoSampler, etc. HunyuanVideo uses HunyuanVideoModelLoader, HunyuanVideoSampler, etc. They have a similar structure but aren’t directly interchangeable.

Q: If I have 16GB VRAM, which should I pick?

A: With 16GB you can run Wan 2.2 14B with sequential_cpu_offload (~15-20 min per clip) or HunyuanVideo with offload (~20-25 min). Wan 14B tends to be faster in practice with offload. If motion quality matters more than speed, go HunyuanVideo.

Conclusion: Make the Right Call

🏆 Our recommendation

The choice between Wan 2.2 and HunyuanVideo isn’t about which is “better” in absolute terms, but which fits your most critical constraint.

• If your GPU has 24GB: HunyuanVideo is the safest bet for professional-quality character motion.
• If you have 16GB and need speed: Wan 14B will give you 90% of the quality in significantly less time.
• If your budget is tight (12GB): Wan 1.3B is still viable for many projects, especially content without complex characters.

Download both models, run a couple of tests with your own content, and compare. The spec sheets are guides, but your critical eye and your deadlines are what ultimately decide the right call.

Keep Reading

If you want to explore more video generation options, check our dedicated Wan 2.2 image-to-video guide and our 5 local AI video models tested on one RTX 3090, which puts Wan 2.2, LTXV-2.3, SCAIL-2, and Wan 2.1 side by side on the same hardware. If GGUF quantization is unfamiliar, our GGUF models in ComfyUI guide explains the trade-offs.