Wan 2.2 I2V 480p LoRA

Wan 2.2 I2V 480p LoRA

Playground

WAN 2.2 A14B Image-to-Video model generates unlimited 480p videos from images and supports custom LoRAs for personalized styles and fine-tuning. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan-2.2-i2v-480p-lora

Wan 2.2 is a multimodal generative video model built with an MoE (Mixture of Experts) architecture, combining high-noise and low-noise experts. This design allows the model to adapt denoising steps and generate cinematic-quality video with fine motion control, complex scene handling, and faithful semantic alignment.

With LoRA support (up to 3 LoRAs per job), Wan 2.2 becomes even more customizable, enabling creators to apply fine-tuned artistic or stylistic layers to their video generations.

• Wan-2.2-i2v-480p-lora-ultra-fast
• Wan-2.2/i2v-480p-ultra-fast

Key Features

• Cinematic-level Aesthetic Control: Professional camera language, multi-dimensional control over lighting, color, and composition.

• Large-scale Complex Motion: Smoothly restores natural motion, supports multi-subject dynamics, and enhances controllability.

• Precise Semantic Compliance: Excels at complex scene understanding and multi-object generation, ensuring faithful creative intent.

• LoRA Integration: Import up to 3 LoRAs per job for both high-noise and low-noise experts, with adjustable blending scale.

Limits and Performance

• Resolution: 480p

• Duration options: 5s or 8s

• Input types:

  • Prompt
  • Image (First Frame)
  • Last Image (Last Frame)

• LoRAs: up to 3 high-noise LoRAs + 3 low-noise LoRAs or just 3 LoRAs

• Seed: reproducibility control

Pricing

How to Use

1. Upload an initial image.
2. Write a prompt describing the video scene.
3. (Optional) Add a last_image for smooth transitions.
4. Select duration (5s or 8s).
5. Add LoRAs (up to 3 for high-noise experts, 3 for low-noise experts).
6. (Optional) Set a seed for reproducibility.
7. Run the job and preview/download your video.

Pro Tips

• Use image + last_image for storyboarding transitions.
• Apply high-noise LoRAs for global style changes, and low-noise LoRAs for subtle refinements.
• Keep LoRA scale values balanced (0.5–1.0 recommended) for natural blending.
• Choose 5s for quick iterations and 8s for polished results.

Note

• If you did not upload the image locally, please ensure that the image URL is accessible! A successfully accessible image will display a preview in the interface.

Reference

• Use your LoRA
• Train your LoRA

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2/i2v-480p-lora" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "duration": 5,
    "seed": -1
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"