---
license: apache-2.0
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
base_model:
- Wan-AI/Wan2.2-I2V-A14B
---
# Wan2.2 I2V LightX2V 2Step
Fast LightX2V LoRAs for **Wan2.2 I2V** image-to-video.
Tuned for **2 steps high + 2 steps low** setup.
___
| File | Load on |
|------|---------|
| `Wan2.2_I2V_LightX2V_2step_high_noise.safetensors` | [High-noise](https://huggingface.co/rzgar/Wan2.2_I2V_LightX2V_2Step/resolve/main/Wan2.2_I2V_LightX2V_2step_high_noise.safetensors) |
| `Wan2.2_I2V_LightX2V_2step_high_noise.safetensors` | [Low-noise](https://huggingface.co/rzgar/Wan2.2_I2V_LightX2V_2Step/resolve/main/Wan2.2_I2V_LightX2V_2step_low_noise.safetensors) |
**Strength: 1.0** on both.
---
## Why use this?
Standard LightX2V workflows run **4 steps per stage**. These LoRAs are tuned so you can run **2 steps per stage** and still get usable motion and prompt follow at roughly half the 4Step time.
On my hardware, 81 f/s:
| Setup | Resolution | Steps | Avg. time |
|-------|------------|-------|-----------|
| Default LightX2V | 512×848 | 4 + 4 | ~**89 s** |
| **This LoRA** | 512×848 | **2 + 2** | ~**37 s** |
The time we spend on a **512×848** clip with 4Step LightX2V is about what it needs for **720×1280** with this pair.
Best when you need **many previews**, prompt tests, or seed hunting, and care more about iteration speed than maximum fine detail.
---
___
Text-to-Video style: [input image](https://huggingface.co/rzgar/Wan2.2_I2V_LightX2V_2Step/resolve/main/video/white_bg.png) | [Prompt](https://huggingface.co/rzgar/Wan2.2_I2V_LightX2V_2Step/resolve/main/video/t2v_style.txt)
___
## Recommended sampling
**Schedulers that work well**
| Sampler | Scheduler |
|---------|-----------|
| `dpmpp_2m_sde` | `sgm_uniform` |
| `dpmpp_2m_sde_heun` | `sgm_uniform` |
| `sa_solver_pece` | `sgm_uniform` |
**Strength:** `1.0` high · `1.0` low
**Steps:** `2` high · `2` low
### Euler / Simple
`euler` + `simple` still works, but **reliability drops**. Expect more duds, often about **2 good out of 4** runs. Prefer the samplers above when you want fewer re-rolls.
---
## Quality expectations
From a small random-seed test set (**9** generations):
| Outcome | Count | Notes |
|---------|-------|-------|
| Clean motion, on-prompt, no body deformation | **6 / 9** | Usable “hero” candidates |
| Mild motion issues | **1 / 9** | Often still salvageable |
| Strong motion error | **2 / 9** | Reroll seed |
So: most seeds are fine, a minority will need a new seed. That trade-off is kinda acceptable for speed.
Compared with full 4-step LightX2V you may lose some fine detail and consistency. For final hero frames, you can still switch back to a 4-step stack.
---
## 🙏 Acknowledgements
[LightX2V](https://huggingface.co/lightx2v) | [Wan-AI](https://huggingface.co/Wan-AI)
---
## Quality expectations
From a small random-seed test set (**9** generations):
| Outcome | Count | Notes |
|---------|-------|-------|
| Clean motion, on-prompt, no body deformation | **6 / 9** | Usable “hero” candidates |
| Mild motion issues | **1 / 9** | Often still salvageable |
| Strong motion error | **2 / 9** | Reroll seed |
So: most seeds are fine, a minority will need a new seed. That trade-off is kinda acceptable for speed.
Compared with full 4-step LightX2V you may lose some fine detail and consistency. For final hero frames, you can still switch back to a 4-step stack.
---
## 🙏 Acknowledgements
[LightX2V](https://huggingface.co/lightx2v) | [Wan-AI](https://huggingface.co/Wan-AI)