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Documentation Index

Fetch the complete documentation index at: https://docs.together.ai/llms.txt

Use this file to discover all available pages before exploring further.

A high level overview of video generation parameters and when to use them. For parameters tied to reference images, keyframes, audio input, or video editing, see Capability-specific parameters at the bottom. For the complete schema, including every supported field along with its types and ranges, see the video generation API reference.
Available parameters vary by model. Wan 2.7 models use resolution and ratio instead of width and height. Kling requires keyframe images via media.frame_images instead of a prompt. See the supported models table for per-model coverage.

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Quick reference

Match the problem you’re solving to the parameter most likely to help.
  • Video doesn’t match the prompt: Make the prompt more specific, add a negative_prompt for what to exclude, or raise guidance_scale toward 9-10.
  • Output looks oversaturated or has weird motion: Lower guidance_scale to 6-7. Avoid values above 12.
  • Poor visual quality: Raise steps to 30-40 for production runs. Diminishing returns past 50.
  • Generation is too slow or expensive while iterating: Lower steps to 10 for quick previews, and shorten seconds.
  • Need the same video every run (evals, regression tests): Set seed to a fixed integer.
  • Wrong dimensions or aspect ratio: Set width and height explicitly. On Wan 2.7, set resolution and ratio instead.
  • Output file is too large: Raise output_quality (higher number means more compression). Lower it for higher fidelity.
  • Need consistent characters or style across the video: Pass media.reference_images. See Reference images and keyframes.
  • Need to pin starting or ending frames: Pass media.frame_images. See Reference images and keyframes.
  • Need lip sync or beat-matched motion: Pass media.audio_inputs. See Video audio input.

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Prompting

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prompt

A description of the video to generate. Required for every model except Kling. Maximum length is 32,000 characters. Be specific about subject, action, setting, camera movement, and pacing. Vague prompts produce generic motion. Include verbs and temporal cues (“slowly pans”, “the camera tracks left”) since video models are sensitive to motion language. Typical default: required.

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negative_prompt

A description of what to avoid in the generated video. Useful for excluding common artifacts. Set it when the model produces unwanted elements (extra limbs, flickering, watermarks). A reasonable starting point: "blurry, low quality, distorted, flickering". Typical default: unset.

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Output dimensions

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width and height

The size of the generated video in pixels. Available combinations differ by model. Typical default: 1366 x 768.

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resolution

A resolution tier used by Wan 2.7 models in place of width and height. Accepts "720P" or "1080P". Typical default: "1080P".

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ratio

The aspect ratio used by Wan 2.7 models. Accepts "16:9", "9:16", "1:1", "4:3", or "3:4". Typical default: "16:9".

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Length and frame rate

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seconds

Clip duration in seconds. Accepted range is "1" through "10". Passed as a string. Longer clips cost more and take longer to generate. Use shorter clips while iterating on prompts and parameters. Typical default: "6".

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fps

Frames per second. Higher values produce smoother motion at the cost of generation time and file size. Typical default: 24 (some models accept up to 60).

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Quality and speed

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steps

The number of denoising steps. More steps generally improve visual quality and temporal consistency at a near-linear cost in latency. Past a model-specific point, additional steps stop helping. Lower it (10) for quick previews. Use 20 for a balanced default. Raise it (30-40) for production runs. Avoid values above 50. Range: 10-50. Typical default: model-specific. 
# Quick preview
job_quick = client.videos.create(
    prompt="A person walking through a forest",
    model="minimax/hailuo-02",
    steps=10,
)

# Production quality
job_production = client.videos.create(
    prompt="A person walking through a forest",
    model="minimax/hailuo-02",
    steps=40,
)

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guidance_scale

Controls how closely the video follows the prompt. Higher values make the model adhere more strictly to the text description. Lower values give the model more creative freedom. Affects both visual content and temporal consistency. Recommended range is 6.0-10.0. Values above 12 may cause over-guidance artifacts or unnatural motion.
  • 6.0-7.0: More creative, less literal.
  • 7.0-9.0: Sweet spot for most use cases.
  • 9.0-10.0: Strict adherence to the prompt.
Typical default: model-specific. 
from together import Together

client = Together()

# Low guidance: more creative interpretation
job_creative = client.videos.create(
    prompt="an astronaut riding a horse on the moon",
    model="minimax/hailuo-02",
    guidance_scale=6.0,
    seed=100,
)

# High guidance: closer to literal prompt
job_literal = client.videos.create(
    prompt="an astronaut riding a horse on the moon",
    model="minimax/hailuo-02",
    guidance_scale=10.0,
    seed=100,
)

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Reproducibility

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seed

An integer that fixes the random initialization. With the same seed, prompt, model, and parameters, the model returns the same video. Useful for reproducibility and for fair comparisons when tuning other parameters. Typical default: unset (each call returns a new video).

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Output format

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output_format

The encoded video format. Accepts "MP4" or "WEBM". MP4 is the broadest-compatible default. WEBM produces smaller files but isn’t supported by every player. Typical default: "MP4".

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output_quality

Compression quality. Lower values produce higher fidelity and larger files. Higher values produce smaller files with more compression artifacts. Typical default: 20.

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Audio

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generate_audio

Whether the model should generate audio for the video. Only applies to models that support audio generation. Typical default: false.

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Capability-specific parameters

ParameterTypeDescriptionDefault
promptstringText description of the video to generate.Required
modelstringModel identifier.Required
widthintegerVideo width in pixels.1366
heightintegerVideo height in pixels.768
secondsstringLength of video (1-10)."6"
fpsintegerFrames per second.15-60
stepsintegerDiffusion steps (higher = better quality, slower).10-50
guidance_scalefloatHow closely to follow prompt.6.0-10.0
seedintegerRandom seed for reproducibility.any
output_formatstringVideo format (MP4, WEBM).MP4
output_qualityintegerBitrate/quality (lower = higher quality).20
negative_promptstringWhat to avoid in generation.-
frame_imagesarrayKeyframe images for video generation. If size 1, starting frame; if size 2, starting and ending frame; if more than 2, frame must be specified per image.
resolutionstringVideo resolution tier (720P, 1080P). Used by Wan 2.7 models instead of width/height."1080P"
ratiostringAspect ratio (16:9, 9:16, 1:1, 4:3, 3:4). Used by Wan 2.7 models."16:9"
mediaobjectMedia inputs for the request (see schema and compatibility below).-
These parameters belong to features with their own dedicated pages. Each link below covers supported models and end-to-end examples. The full media object schema is documented in the next subsection.
  • media.frame_images: Pin specific frames to known images (keyframes). See Reference images and keyframes.
  • media.reference_images and media.reference_videos: Steer visual style with references that should appear consistently across the video. See Reference images and keyframes.
  • media.audio_inputs: Drive generation with an audio file for lip sync, beat-matched motion, or narration. See Video audio input.
  • media.source_video and media.frame_videos: Edit or extend an existing clip. Wan 2.7 specific. See the Wan 2.7 quickstart.
The top-level frame_images and reference_images parameters are deprecated. Use media.frame_images and media.reference_images instead.

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media object schema

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": []
  }
}
FieldTypeDescription
frame_imagesarrayKeyframe images for I2V. Each item: {input_image, frame} where frame is "first" or "last".
frame_videosarrayInput video clips for video continuation (I2V). Each item: {video: "url"}.
reference_imagesarrayReference images for character or object consistency (R2V) or visual guidance (Video Edit).
reference_videosarrayReference videos for character or object consistency (R2V). Each item: {video: "url"}.
source_videostringSource video URL to edit (Video Edit).
audio_inputsarrayAudio file URLs to drive generation (lip sync, beat-matched motion, etc.) for T2V and I2V. Each item: "url". WAV or MP3, 3-30s, up to 15 MB.
Not all media fields are supported on every model. See the Wan 2.7 quickstart for field compatibility across Wan 2.7 models.

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See also