Wan 2.2 I2V 480p LoRA Ultra Fast

Wan 2.2 I2V 480p LoRA Ultra Fast

Playground

Wan 2.2 i2v delivers ultra-fast Image-to-Video at 480p with support for custom LoRAs for tailored styles. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.2 (Ultra-Fast 480p, with LoRA) is a high-speed multimodal video generation model. It delivers cinematic-quality results at ultra-fast inference speed, with support for up to 3 LoRAs per job for flexible style and character control.

• Wan-2.2-i2v-480p-lora
• 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

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "duration": 5,
  "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2/i2v-480p-lora-ultra-fast" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters