Alibaba

Wan 2.6

Name: Wan 2.6
Brand: Alibaba
Price: 0.03 USD
Availability: InStock

AI Image & Video Model

Image Video Featured #9 Image-to-Image

Alibaba's multimodal generation model from the Wan AI suite, supporting text-to-video, image-to-video, reference-to-video with audio, and text-to-image, in both Chinese and English

Wan 2.6 API Image & Video generation

Integrate Wan 2.6 into your workflow for text-to-image generation and advanced image editing via Lumenfall's unified OpenAI-compatible API. This endpoint supports both direct text prompting and reference image guidance to maintain stylistic consistency across your generated media.

Base URL

https://api.lumenfall.ai/openai/v1 Image

https://api.lumenfall.ai/v1 Video

Model

wan-2.6

Code Examples

Text to Image

/v1/images/generations

curl -X POST \

  https://api.lumenfall.ai/openai/v1/images/generations \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "wan-2.6",

    "prompt": "",

    "size": "1024x1024"

}'

# Response:

# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

import OpenAI from 'openai';

const client = new OpenAI({

  apiKey: 'YOUR_API_KEY',

  baseURL: 'https://api.lumenfall.ai/openai/v1'

});

const response = await client.images.generate({

  model: 'wan-2.6',

  prompt: '',

  size: '1024x1024'

});

// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

console.log(response.data[0].url);

from openai import OpenAI

client = OpenAI(

    api_key="YOUR_API_KEY",

    base_url="https://api.lumenfall.ai/openai/v1"

response = client.images.generate(

    model="wan-2.6",

    prompt="",

    size="1024x1024"

# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

print(response.data[0].url)

Image Edit

/v1/images/edits

curl -X POST \

  https://api.lumenfall.ai/openai/v1/images/edits \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -F "model=wan-2.6" \

  -F "[email protected]" \

  -F "prompt=Add a starry night sky to this image" \

  -F "size=1024x1024"

# Response:

# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

import OpenAI from 'openai';

import fs from 'fs';

const client = new OpenAI({

  apiKey: 'YOUR_API_KEY',

  baseURL: 'https://api.lumenfall.ai/openai/v1'

});

const response = await client.images.edit({

  model: 'wan-2.6',

  image: fs.createReadStream('source.png'),

  prompt: 'Add a starry night sky to this image',

  size: '1024x1024'

});

// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

console.log(response.data[0].url);

from openai import OpenAI

client = OpenAI(

    api_key="YOUR_API_KEY",

    base_url="https://api.lumenfall.ai/openai/v1"

response = client.images.edit(

    model="wan-2.6",

    image=open("source.png", "rb"),

    prompt="Add a starry night sky to this image",

    size="1024x1024"

# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

print(response.data[0].url)

Text to Video

/v1/videos/generations

# Step 1: Submit video generation request

VIDEO_ID=$(curl -s -X POST \

  https://api.lumenfall.ai/v1/videos \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "wan-2.6",

    "prompt": "",

    "size": "1024x1024"

  }' | jq -r '.id')

echo "Video ID: $VIDEO_ID"

# Step 2: Poll for completion

while true; do

  RESULT=$(curl -s \

    https://api.lumenfall.ai/v1/videos/$VIDEO_ID \

    -H "Authorization: Bearer $LUMENFALL_API_KEY")

  STATUS=$(echo $RESULT | jq -r '.status')

  echo "Status: $STATUS"

  if [ "$STATUS" = "completed" ]; then

    echo $RESULT | jq -r '.output.url'

    break

  elif [ "$STATUS" = "failed" ]; then

    echo $RESULT | jq -r '.error.message'

    break

fi

  sleep 5

done

const BASE_URL = 'https://api.lumenfall.ai/v1';

const API_KEY = 'YOUR_API_KEY';

// Step 1: Submit video generation request

const submitRes = await fetch(`${BASE_URL}/videos`, {

  method: 'POST',

  headers: {

    'Authorization': `Bearer ${API_KEY}`,

    'Content-Type': 'application/json'

},

  body: JSON.stringify({

    model: 'wan-2.6',

    prompt: '',

    size: '1024x1024'

})

});

const { id: videoId } = await submitRes.json();

console.log('Video ID:', videoId);

// Step 2: Poll for completion

while (true) {

  const pollRes = await fetch(`${BASE_URL}/videos/${videoId}`, {

    headers: { 'Authorization': `Bearer ${API_KEY}` }

});

  const result = await pollRes.json();

  if (result.status === 'completed') {

    console.log('Video URL:', result.output.url);

    break;

  } else if (result.status === 'failed') {

    console.error('Error:', result.error.message);

    break;

  await new Promise(r => setTimeout(r, 5000));

import requests

import time

BASE_URL = "https://api.lumenfall.ai/v1"

API_KEY = "YOUR_API_KEY"

HEADERS = {

    "Authorization": f"Bearer {API_KEY}",

    "Content-Type": "application/json"

# Step 1: Submit video generation request

response = requests.post(

    f"{BASE_URL}/videos",

    headers=HEADERS,

    json={

        "model": "wan-2.6",

        "prompt": "",

        "size": "1024x1024"

video_id = response.json()["id"]

print(f"Video ID: {video_id}")

# Step 2: Poll for completion

while True:

    result = requests.get(

        f"{BASE_URL}/videos/{video_id}",

        headers=HEADERS

    ).json()

    if result["status"] == "completed":

        print(f"Video URL: {result['output']['url']}")

        break

    elif result["status"] == "failed":

        print(f"Error: {result['error']['message']}")

        break

    time.sleep(5)

Image to Video

/v1/videos/generations

# Step 1: Submit image-to-video request

VIDEO_ID=$(curl -s -X POST \

  https://api.lumenfall.ai/v1/videos \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "wan-2.6",

    "prompt": "",

    "image_url": "https://example.com/start-frame.jpg",

    "duration": "10",

    "aspect_ratio": "16:9"

  }' | jq -r '.id')

echo "Video ID: $VIDEO_ID"

# Step 2: Poll for completion

while true; do

  RESULT=$(curl -s \

    https://api.lumenfall.ai/v1/videos/$VIDEO_ID \

    -H "Authorization: Bearer $LUMENFALL_API_KEY")

  STATUS=$(echo $RESULT | jq -r '.status')

  echo "Status: $STATUS"

  if [ "$STATUS" = "completed" ]; then

    echo $RESULT | jq -r '.output.url'

    break

  elif [ "$STATUS" = "failed" ]; then

    echo $RESULT | jq -r '.error.message'

    break

fi

  sleep 5

done

const BASE_URL = 'https://api.lumenfall.ai/v1';

const API_KEY = 'YOUR_API_KEY';

// Step 1: Submit image-to-video request

const submitRes = await fetch(`${BASE_URL}/videos`, {

  method: 'POST',

  headers: {

    'Authorization': `Bearer ${API_KEY}`,

    'Content-Type': 'application/json'

},

  body: JSON.stringify({

    model: 'wan-2.6',

    prompt: '',

    image_url: 'https://example.com/start-frame.jpg',

    duration: '10',

    aspect_ratio: '16:9'

})

});

const { id: videoId } = await submitRes.json();

console.log('Video ID:', videoId);

// Step 2: Poll for completion

while (true) {

  const pollRes = await fetch(`${BASE_URL}/videos/${videoId}`, {

    headers: { 'Authorization': `Bearer ${API_KEY}` }

});

  const result = await pollRes.json();

  if (result.status === 'completed') {

    console.log('Video URL:', result.output.url);

    break;

  } else if (result.status === 'failed') {

    console.error('Error:', result.error.message);

    break;

  await new Promise(r => setTimeout(r, 5000));

import requests

import time

BASE_URL = "https://api.lumenfall.ai/v1"

API_KEY = "YOUR_API_KEY"

HEADERS = {

    "Authorization": f"Bearer {API_KEY}",

    "Content-Type": "application/json"

# Step 1: Submit image-to-video request

response = requests.post(

    f"{BASE_URL}/videos",

    headers=HEADERS,

    json={

        "model": "wan-2.6",

        "prompt": "",

        "image_url": "https://example.com/start-frame.jpg",

        "duration": "10",

        "aspect_ratio": "16:9"

video_id = response.json()["id"]

print(f"Video ID: {video_id}")

# Step 2: Poll for completion

while True:

    result = requests.get(

        f"{BASE_URL}/videos/{video_id}",

        headers=HEADERS

    ).json()

    if result["status"] == "completed":

        print(f"Video URL: {result['output']['url']}")

        break

    elif result["status"] == "failed":

        print(f"Error: {result['error']['message']}")

        break

    time.sleep(5)

Video to Video

/v1/videos/generations

# Step 1: Submit video-to-video request

VIDEO_ID=$(curl -s -X POST \

  https://api.lumenfall.ai/v1/videos \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "wan-2.6",

    "prompt": "Apply cinematic color grading to @Video1",

    "video_url": "https://example.com/source.mp4",

    "keep_audio": true,

    "aspect_ratio": "16:9"

  }' | jq -r '.id')

echo "Video ID: $VIDEO_ID"

# Step 2: Poll for completion

while true; do

  RESULT=$(curl -s \

    https://api.lumenfall.ai/v1/videos/$VIDEO_ID \

    -H "Authorization: Bearer $LUMENFALL_API_KEY")

  STATUS=$(echo $RESULT | jq -r '.status')

  echo "Status: $STATUS"

  if [ "$STATUS" = "completed" ]; then

    echo $RESULT | jq -r '.output.url'

    break

  elif [ "$STATUS" = "failed" ]; then

    echo $RESULT | jq -r '.error.message'

    break

fi

  sleep 5

done

const BASE_URL = 'https://api.lumenfall.ai/v1';

const API_KEY = 'YOUR_API_KEY';

// Step 1: Submit video-to-video request

const submitRes = await fetch(`${BASE_URL}/videos`, {

  method: 'POST',

  headers: {

    'Authorization': `Bearer ${API_KEY}`,

    'Content-Type': 'application/json'

},

  body: JSON.stringify({

    model: 'wan-2.6',

    prompt: 'Apply cinematic color grading to @Video1',

    video_url: 'https://example.com/source.mp4',

    keep_audio: true,

    aspect_ratio: '16:9'

})

});

const { id: videoId } = await submitRes.json();

console.log('Video ID:', videoId);

// Step 2: Poll for completion

while (true) {

  const pollRes = await fetch(`${BASE_URL}/videos/${videoId}`, {

    headers: { 'Authorization': `Bearer ${API_KEY}` }

});

  const result = await pollRes.json();

  if (result.status === 'completed') {

    console.log('Video URL:', result.output.url);

    break;

  } else if (result.status === 'failed') {

    console.error('Error:', result.error.message);

    break;

  await new Promise(r => setTimeout(r, 5000));

import requests

import time

BASE_URL = "https://api.lumenfall.ai/v1"

API_KEY = "YOUR_API_KEY"

HEADERS = {

    "Authorization": f"Bearer {API_KEY}",

    "Content-Type": "application/json"

# Step 1: Submit video-to-video request

response = requests.post(

    f"{BASE_URL}/videos",

    headers=HEADERS,

    json={

        "model": "wan-2.6",

        "prompt": "Apply cinematic color grading to @Video1",

        "video_url": "https://example.com/source.mp4",

        "keep_audio": True,

        "aspect_ratio": "16:9"

video_id = response.json()["id"]

print(f"Video ID: {video_id}")

# Step 2: Poll for completion

while True:

    result = requests.get(

        f"{BASE_URL}/videos/{video_id}",

        headers=HEADERS

    ).json()

    if result["status"] == "completed":

        print(f"Video URL: {result['output']['url']}")

        break

    elif result["status"] == "failed":

        print(f"Error: {result['error']['message']}")

        break

    time.sleep(5)

Parameter Reference

Required Supported Not available

Core Parameters

Parameter	Type	Description	Modes
`prompt`	string	Required. Text prompt for image generation	T2I Edit T2V I2V V2V
`negative_prompt`	string	Negative prompt to guide generation away from undesired content	T2I Edit T2V I2V V2V
`seed`	integer	Random seed for reproducibility	T2I Edit T2V I2V V2V

Size & Layout

Parameter	Type	Description	Modes
`size`	string	Image dimensions as WxH pixels (e.g. "1024x1024") or aspect ratio (e.g. "16:9") WxH determines both shape and scale (aspect_ratio and resolution are ignored when size is provided). W:H format is equivalent to aspect_ratio.	T2I Edit T2V I2V V2V
`aspect_ratio`	string	Aspect ratio of the output image (e.g. "16:9", "1:1") Controls shape independently of scale. Use with resolution to control both. If size is also provided, size takes precedence. Any ratio is accepted and mapped to the nearest supported value.	T2I Edit T2V I2V V2V
`resolution`	string	Output resolution tier (e.g. "1K", "4K") Controls scale independently of shape. Higher tiers produce larger images and cost more. If size is also provided, size takes precedence for scale. Any tier is accepted and mapped to the nearest supported value.	T2I Edit T2V I2V V2V

size

Exact pixel dimensions

"1920x1080"

aspect_ratio

Shape only, default scale

"16:9"

resolution

Scale tier, preserves shape

"1K"

Priority when combined

size › aspect_ratio + resolution › aspect_ratio › resolution

size is most specific and always wins. aspect_ratio and resolution control shape and scale independently.

How matching works

Shape matching – we pick the closest supported ratio. Ask for 7:1 on a model with 4:1 and 8:1, you get 8:1.

Scale matching – providers use different tier formats: K tiers (0.5K 1K 2K 4K) or megapixel tiers (0.25 1). If the exact tier isn't available, you get the nearest one.

Dimension clamping – if a model has pixel limits, we clamp dimensions to fit and keep the aspect ratio intact.

Media Inputs

Parameter	Type	Description	Modes
`image`	file	Required. Input image(s) to edit Supports PNG, JPEG, WebP.	T2I Edit T2V I2V V2V

Output & Format

Parameter	Type	Description	Modes
`response_format`	string	How to return the image `url` `b64_json` Default: `"url"`	T2I Edit T2V I2V V2V
`output_format`	string	Output image format `png` `jpeg` `gif` `webp` `avif` Gateway converts to requested format if provider doesn't support it natively.	T2I Edit T2V I2V V2V
`output_compression`	integer	Compression level for lossy formats (JPEG, WebP, AVIF)	T2I Edit T2V I2V V2V
`n`	integer	Number of images to generate Default: `1` Gateway generates multiple images in parallel even if provider only supports 1.	T2I Edit T2V I2V V2V

Additional Parameters

Parameter	Type	Description	Modes
`input_reference`	array	Input image(s) to animate into video	T2I Edit T2V I2V V2V
`input_video`	string	Input video URL to transform	T2I Edit T2V I2V V2V
`enable_prompt_expansion` fal	boolean	Enable LLM prompt optimization. Significantly improves results for simple prompts but adds 3-4 seconds processing time.	T2I Edit T2V I2V V2V
`enable_safety_checker` fal	boolean	Enable content moderation for input and output.	T2I Edit T2V I2V V2V

Parameter Normalization

How we handle parameters across different providers

Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:

Behavior	What happens	Example
`passthrough`	Sent as-is to the provider	style, quality
`renamed`	Same value, mapped to the field name the provider expects	prompt
`converted`	Transformed to the provider's native format	size
`emulated`	Works even if the provider has no concept of it	n, response_format

Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.

Full API Reference Authentication, endpoints, and more