Wan 2.7 quickstart

Wan 2.7

Wan 2.7 is a family of video generation models supporting text-to-video, image-to-video with keyframe control, reference-based character/object consistency, and video editing. All models output 720P or 1080P video at 30fps in MP4 format.

Model	API String	Best For	Duration
Wan 2.7 T2V	`Wan-AI/wan2.7-t2v`	Text-to-video with audio	Up to 15s
Wan 2.7 I2V	`Wan-AI/wan2.7-i2v`	Image-to-video, keyframe control, video continuation	Up to 15s
Wan 2.7 R2V	`Wan-AI/wan2.7-r2v`	Character/object consistency from reference images or videos	Up to 10s
Wan 2.7 Video Edit	`Wan-AI/wan2.7-videoedit`	Instruction-based editing, style transfer	Up to 10s

Text-to-Video

Generate a video from a text prompt. Video generation is asynchronous — you create a job, receive a job ID, and poll for the result.

import time
from together import Together

client = Together()

job = client.videos.create(
    prompt="A small cute cartoon kitten general in golden armor stands on a cliff, commanding an army of mice charging below. Epic ancient war atmosphere, dramatic clouds over snowy mountains.",
    model="Wan-AI/wan2.7-t2v",
    resolution="720P",
    ratio="16:9",
    seconds="10",
)

print(f"Job ID: {job.id}")

while True:
    status = client.videos.retrieve(job.id)
    print(f"Status: {status.status}")

    if status.status == "completed":
        print(f"Video URL: {status.outputs.video_url}")
        break
    elif status.status == "failed":
        print(f"Error: {status.error}")
        break

    time.sleep(60)

import Together from "together-ai";

const together = new Together();

async function main() {
  const job = await together.videos.create({
    prompt: "A small cute cartoon kitten general in golden armor stands on a cliff, commanding an army of mice charging below. Epic ancient war atmosphere, dramatic clouds over snowy mountains.",
    model: "Wan-AI/wan2.7-t2v",
    resolution: "720P",
    ratio: "16:9",
    seconds: "10",
  });

  console.log(`Job ID: ${job.id}`);

  while (true) {
    const status = await together.videos.retrieve(job.id);
    console.log(`Status: ${status.status}`);

    if (status.status === "completed") {
      console.log(`Video URL: ${status.outputs.video_url}`);
      break;
    } else if (status.status === "failed") {
      console.log(`Error: ${JSON.stringify(status.error)}`);
      break;
    }

    await new Promise((resolve) => setTimeout(resolve, 60000));
  }
}

main();

curl -X POST "https://api.together.ai/v2/videos" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Wan-AI/wan2.7-t2v",
    "prompt": "A small cute cartoon kitten general in golden armor stands on a cliff, commanding an army of mice charging below. Epic ancient war atmosphere, dramatic clouds over snowy mountains.",
    "resolution": "720P",
    "ratio": "16:9",
    "seconds": "10"
  }'

Text-to-Video with Audio

Drive video generation with an audio file using media.audio_inputs. The model synchronizes the generated video to the audio — useful for lip sync, beat-matched motion, or narration-driven scenes. If no audio is provided, the model automatically generates matching background music or sound effects.

import time
from together import Together

client = Together()

job = client.videos.create(
    prompt="A graffiti character comes to life off a concrete wall, rapping energetically under an urban railway bridge at night, lit by a lone streetlamp.",
    model="Wan-AI/wan2.7-t2v",
    resolution="720P",
    ratio="16:9",
    seconds="10",
    media={
        "audio_inputs": [
            "https://example.com/rap-audio.mp3",
        ],
    },
)

print(f"Job ID: {job.id}")

while True:
    status = client.videos.retrieve(job.id)
    print(f"Status: {status.status}")

    if status.status == "completed":
        print(f"Video URL: {status.outputs.video_url}")
        break
    elif status.status == "failed":
        print(f"Error: {status.error}")
        break

    time.sleep(60)

import Together from "together-ai";

const together = new Together();

async function main() {
  const job = await together.videos.create({
    prompt: "A graffiti character comes to life off a concrete wall, rapping energetically under an urban railway bridge at night, lit by a lone streetlamp.",
    model: "Wan-AI/wan2.7-t2v",
    resolution: "720P",
    ratio: "16:9",
    seconds: "10",
    media: {
      audio_inputs: [
        "https://example.com/rap-audio.mp3",
      ],
    },
  });

  console.log(`Job ID: ${job.id}`);

  while (true) {
    const status = await together.videos.retrieve(job.id);
    console.log(`Status: ${status.status}`);

    if (status.status === "completed") {
      console.log(`Video URL: ${status.outputs.video_url}`);
      break;
    } else if (status.status === "failed") {
      console.log(`Error: ${JSON.stringify(status.error)}`);
      break;
    }

    await new Promise((resolve) => setTimeout(resolve, 60000));
  }
}

main();

Audio constraints: WAV or MP3 format, 3-30 seconds, up to 15 MB. If the audio is longer than the video duration, it will be truncated. If shorter, the remaining portion of the video will be silent.

Image-to-Video

Animate a still image by using it as the first frame. Pass images via media.frame_images with frame set to "first" or "last".

import time
from together import Together

client = Together()

job = client.videos.create(
    prompt="A black cat curiously gazes up at the sky. The camera slowly rises from eye level to a bird's-eye view, capturing the cat's curious eyes.",
    model="Wan-AI/wan2.7-i2v",
    resolution="720P",
    ratio="16:9",
    seconds="5",
    media={
        "frame_images": [
            {
                "input_image": "https://example.com/cat.png",
                "frame": "first",
            }
        ],
    },
)

print(f"Job ID: {job.id}")

while True:
    status = client.videos.retrieve(job.id)
    print(f"Status: {status.status}")

    if status.status == "completed":
        print(f"Video URL: {status.outputs.video_url}")
        break
    elif status.status == "failed":
        print(f"Error: {status.error}")
        break

    time.sleep(60)

import Together from "together-ai";

const together = new Together();

async function main() {
  const job = await together.videos.create({
    prompt: "A black cat curiously gazes up at the sky. The camera slowly rises from eye level to a bird's-eye view, capturing the cat's curious eyes.",
    model: "Wan-AI/wan2.7-i2v",
    resolution: "720P",
    ratio: "16:9",
    seconds: "5",
    media: {
      frame_images: [{
        input_image: "https://example.com/cat.png",
        frame: "first",
      }],
    },
  });

  console.log(`Job ID: ${job.id}`);

  while (true) {
    const status = await together.videos.retrieve(job.id);
    console.log(`Status: ${status.status}`);

    if (status.status === "completed") {
      console.log(`Video URL: ${status.outputs.video_url}`);
      break;
    } else if (status.status === "failed") {
      console.log(`Error: ${JSON.stringify(status.error)}`);
      break;
    }

    await new Promise((resolve) => setTimeout(resolve, 60000));
  }
}

main();

curl -X POST "https://api.together.ai/v2/videos" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Wan-AI/wan2.7-i2v",
    "prompt": "A black cat curiously gazes up at the sky. The camera slowly rises from eye level to an overhead view.",
    "media": {
      "frame_images": [
        {
          "input_image": "https://example.com/cat.png",
          "frame": "first"
        }
      ]
    }
  }'

First and Last Frame Control

Provide both a starting and ending frame to control the video’s transition. The model generates smooth motion between the two keyframes.

import time
from together import Together

client = Together()

job = client.videos.create(
    prompt="Smooth cinematic transition with natural motion",
    model="Wan-AI/wan2.7-i2v",
    resolution="720P",
    ratio="16:9",
    seconds="5",
    media={
        "frame_images": [
            {"input_image": "https://example.com/start.png", "frame": "first"},
            {"input_image": "https://example.com/end.png", "frame": "last"},
        ],
    },
)

print(f"Job ID: {job.id}")

while True:
    status = client.videos.retrieve(job.id)
    print(f"Status: {status.status}")

    if status.status == "completed":
        print(f"Video URL: {status.outputs.video_url}")
        break
    elif status.status == "failed":
        print(f"Error: {status.error}")
        break

    time.sleep(60)

import Together from "together-ai";

const together = new Together();

async function main() {
  const job = await together.videos.create({
    prompt: "Smooth cinematic transition with natural motion",
    model: "Wan-AI/wan2.7-i2v",
    resolution: "720P",
    ratio: "16:9",
    seconds: "5",
    media: {
      frame_images: [
        { input_image: "https://example.com/start.png", frame: "first" },
        { input_image: "https://example.com/end.png", frame: "last" },
      ],
    },
  });

  console.log(`Job ID: ${job.id}`);

  while (true) {
    const status = await together.videos.retrieve(job.id);
    console.log(`Status: ${status.status}`);

    if (status.status === "completed") {
      console.log(`Video URL: ${status.outputs.video_url}`);
      break;
    } else if (status.status === "failed") {
      console.log(`Error: ${JSON.stringify(status.error)}`);
      break;
    }

    await new Promise((resolve) => setTimeout(resolve, 60000));
  }
}

main();

Video Continuation

Continue from an existing video clip using media.frame_videos. The model generates new content that seamlessly extends the input video.

import time
from together import Together

client = Together()

job = client.videos.create(
    prompt="A dog wearing sunglasses skateboarding down a street, 3D cartoon style.",
    model="Wan-AI/wan2.7-i2v",
    resolution="720P",
    ratio="16:9",
    seconds="15",
    media={
        "frame_videos": [
            {"video": "https://example.com/skateboarding-clip.mp4"},
        ],
    },
)

print(f"Job ID: {job.id}")

while True:
    status = client.videos.retrieve(job.id)
    print(f"Status: {status.status}")

    if status.status == "completed":
        print(f"Video URL: {status.outputs.video_url}")
        break
    elif status.status == "failed":
        print(f"Error: {status.error}")
        break

    time.sleep(60)

import Together from "together-ai";

const together = new Together();

async function main() {
  const job = await together.videos.create({
    prompt: "A dog wearing sunglasses skateboarding down a street, 3D cartoon style.",
    model: "Wan-AI/wan2.7-i2v",
    resolution: "720P",
    ratio: "16:9",
    seconds: "15",
    media: {
      frame_videos: [
        { video: "https://example.com/skateboarding-clip.mp4" },
      ],
    },
  });

  console.log(`Job ID: ${job.id}`);

  while (true) {
    const status = await together.videos.retrieve(job.id);
    console.log(`Status: ${status.status}`);

    if (status.status === "completed") {
      console.log(`Video URL: ${status.outputs.video_url}`);
      break;
    } else if (status.status === "failed") {
      console.log(`Error: ${JSON.stringify(status.error)}`);
      break;
    }

    await new Promise((resolve) => setTimeout(resolve, 60000));
  }
}

main();

Reference-to-Video

Generate video featuring a specific person or object by providing reference images or videos via media.reference_images or media.reference_videos. The model maintains the character’s appearance throughout the generated video. Multiple references can be passed for multi-character scenes.

import time
from together import Together

client = Together()

job = client.videos.create(
    prompt="A person dancing on stage",
    model="Wan-AI/wan2.7-r2v",
    resolution="1080P",
    ratio="16:9",
    seconds="5",
    media={
        "reference_videos": [
            {"video": "https://example.com/character-reference.mp4"},
        ],
    },
)

print(f"Job ID: {job.id}")

while True:
    status = client.videos.retrieve(job.id)
    print(f"Status: {status.status}")

    if status.status == "completed":
        print(f"Video URL: {status.outputs.video_url}")
        break
    elif status.status == "failed":
        print(f"Error: {status.error}")
        break

    time.sleep(60)

import Together from "together-ai";

const together = new Together();

async function main() {
  const job = await together.videos.create({
    prompt: "A person dancing on stage",
    model: "Wan-AI/wan2.7-r2v",
    resolution: "1080P",
    ratio: "16:9",
    seconds: "5",
    media: {
      reference_videos: [
        { video: "https://example.com/character-reference.mp4" },
      ],
    },
  });

  console.log(`Job ID: ${job.id}`);

  while (true) {
    const status = await together.videos.retrieve(job.id);
    console.log(`Status: ${status.status}`);

    if (status.status === "completed") {
      console.log(`Video URL: ${status.outputs.video_url}`);
      break;
    } else if (status.status === "failed") {
      console.log(`Error: ${JSON.stringify(status.error)}`);
      break;
    }

    await new Promise((resolve) => setTimeout(resolve, 60000));
  }
}

main();

curl -X POST "https://api.together.ai/v2/videos" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Wan-AI/wan2.7-r2v",
    "prompt": "A person dancing on stage",
    "resolution": "1080P",
    "seconds": 10,
    "media": {
      "reference_videos": [
        {"video": "https://example.com/character-reference.mp4"}
      ]
    }
  }'

Video Editing

Edit an existing video with text instructions using media.source_video. Optionally pass media.reference_images to guide the edit with a visual reference.

import time
from together import Together

client = Together()

job = client.videos.create(
    prompt="Replace the background with the ocean",
    model="Wan-AI/wan2.7-videoedit",
    resolution="720P",
    ratio="16:9",
    media={
        "source_video": "https://example.com/input-video.mp4",
    },
)

print(f"Job ID: {job.id}")

while True:
    status = client.videos.retrieve(job.id)
    print(f"Status: {status.status}")

    if status.status == "completed":
        print(f"Video URL: {status.outputs.video_url}")
        break
    elif status.status == "failed":
        print(f"Error: {status.error}")
        break

    time.sleep(60)

import Together from "together-ai";

const together = new Together();

async function main() {
  const job = await together.videos.create({
    prompt: "Replace the background with the ocean",
    model: "Wan-AI/wan2.7-videoedit",
    resolution: "720P",
    ratio: "16:9",
    media: {
      source_video: "https://example.com/input-video.mp4",
    },
  });

  console.log(`Job ID: ${job.id}`);

  while (true) {
    const status = await together.videos.retrieve(job.id);
    console.log(`Status: ${status.status}`);

    if (status.status === "completed") {
      console.log(`Video URL: ${status.outputs.video_url}`);
      break;
    } else if (status.status === "failed") {
      console.log(`Error: ${JSON.stringify(status.error)}`);
      break;
    }

    await new Promise((resolve) => setTimeout(resolve, 60000));
  }
}

main();

curl -X POST "https://api.together.ai/v2/videos" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Wan-AI/wan2.7-videoedit",
    "prompt": "Replace the background with the ocean",
    "resolution": "720P",
    "media": {
      "source_video": "https://example.com/input-video.mp4"
    }
  }'

Parameters

Parameter	Type	Description	Default
`prompt`	string	Text description of the video to generate (up to 5,000 characters)	Required
`model`	string	Model identifier (see model table above)	Required
`resolution`	string	Video resolution tier (`720P`, `1080P`)	`"1080P"`
`ratio`	string	Aspect ratio (`16:9`, `9:16`, `1:1`, `4:3`, `3:4`)	`"16:9"`
`seconds`	string	Video duration in seconds. T2V and I2V: 2-15. R2V and Video Edit: 2-10.	`"5"`
`seed`	integer	Random seed for reproducibility (0-2,147,483,647)	Random
`negative_prompt`	string	Elements to exclude from generation (up to 500 characters)	-
`media`	object	Media inputs for the request (see schema and compatibility below)	-

Media Object

The media object is the unified way to pass images, videos, and audio into video generation requests.

{
  "prompt": "...",
  "model": "...",
  "media": {
    "frame_images": [],
    "frame_videos": [],
    "reference_images": [],
    "reference_videos": [],
    "source_video": "",
    "audio_inputs": []
  }
}

Field	Type	Description
`frame_images`	array	Keyframe images for I2V. Each item: `{input_image, frame}` where `frame` is `"first"` or `"last"`.
`frame_videos`	array	Input video clips for video continuation (I2V). Each item: `{video: "url"}`.
`reference_images`	array	Reference images for character/object consistency (R2V) or visual guidance (Video Edit).
`reference_videos`	array	Reference videos for character/object consistency (R2V). Each item: `{video: "url"}`.
`source_video`	string	Source video URL to edit (Video Edit).
`audio_inputs`	array	Audio file URLs to drive generation — lip sync, beat-matched motion, etc. (T2V, I2V). Each item: `"url"`. WAV or MP3, 3-30s, up to 15 MB.

Media Compatibility by Model

Not all media fields are supported on every model. Unsupported fields are rejected.

`media` field	T2V	I2V	R2V	Video Edit
`frame_images`	-	First and/or last frame	-	-
`frame_videos`	-	Single video clip	-	-
`reference_images`	-	-	Multiple	Single
`reference_videos`	-	-	Multiple	-
`source_video`	-	-	-	Single (required)
`audio_inputs`	Single	Single	-	-

Prompting Tips

Wan 2.7 supports both Chinese and English prompts. Detailed, descriptive prompts produce the best results — include subject, action, style, camera movement, and atmosphere.

Write descriptive prompts: Instead of “a cat walking,” try “A small black cat walks gracefully through a sunlit garden, soft bokeh background, gentle breeze rustling the flowers, cinematic slow motion.” Use negative prompts to avoid common artifacts:

low resolution, errors, worst quality, low quality, incomplete, extra fingers, bad proportions, blurry, distorted

Control aspect ratio and resolution: Use resolution and ratio to set output dimensions:

Aspect Ratio	720P Dimensions	1080P Dimensions
16:9	1280x720	1920x1080
9:16	720x1280	1080x1920
1:1	960x960	1440x1440
4:3	1104x832	1648x1248
3:4	832x1104	1248x1648

Next Steps

Video Generation Overview — Full parameter reference and supported models
API Reference: Create Video — REST API details
API Reference: Get Video Status — Polling and status codes

GUIDES

MODEL QUICKSTARTS

BUILD APPS

BUILD AGENTS

WORK WITH CODING AGENTS

RAG & SEARCH

SDK INTEGRATIONS

DEDICATED CONTAINERS

Wan 2.7

Text-to-Video

Text-to-Video with Audio

Image-to-Video

First and Last Frame Control

Video Continuation

Reference-to-Video

Video Editing

Parameters

Media Object

Media Compatibility by Model

Prompting Tips

Next Steps

​Wan 2.7

​Text-to-Video

​Text-to-Video with Audio

​Image-to-Video

​First and Last Frame Control

​Video Continuation

​Reference-to-Video

​Video Editing

​Parameters

​Media Object

​Media Compatibility by Model

​Prompting Tips

​Next Steps

Wan 2.7

Text-to-Video

Text-to-Video with Audio

Image-to-Video

First and Last Frame Control

Video Continuation

Reference-to-Video

Video Editing

Parameters

Media Object

Media Compatibility by Model

Prompting Tips

Next Steps