Models

Model Schemas

Understand how model input and output schemas work, and how they differ across model types.

How Schemas Work

Every model on Skytells publishes a JSON Schema for its input and output. When you create a prediction, the input object you send must conform to the model's input_schema. The response will match the output_schema.

You can retrieve any model's schema programmatically:

Get all models
curl https://api.skytells.ai/v1/models \
  -H "x-api-key: YOUR_API_KEY"

Or fetch a single model's schema by slug (GET /v1/models/{slug}):

Get a single model with schemas
curl "https://api.skytells.ai/v1/models/truefusion?fields=input_schema,output_schema" \
  -H "x-api-key: YOUR_API_KEY"

Each model in the response includes input_schema and output_schema fields.


Input Schema Structure

Input schemas follow JSON Schema conventions:

{
  "type": "object",
  "title": "Input",
  "required": ["prompt"],
  "properties": {
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "description": "Text prompt for generation",
      "x-order": 0
    },
    "aspect_ratio": {
      "type": "string",
      "enum": ["1:1", "16:9", "9:16"],
      "default": "1:1",
      "x-order": 1
    }
  }
}

Key fields:

FieldMeaning
requiredParameters you must include in your request
typeData type — string, integer, number, boolean, array
enumFixed set of allowed values
defaultValue used if you omit the parameter
minimum / maximumNumeric bounds
formatSpecial format — uri for URLs, password for secrets
x-orderDisplay ordering hint

Schema Complexity by Model Tier

Models range from minimal to highly configurable schemas. Here's how complexity scales:

Minimal schema (2–4 parameters)

Models like TrueFusion, Imagen 3, and Imagen 4 have streamlined schemas—just prompt, aspect_ratio, and maybe a negative_prompt or safety filter. These are ideal when you want fast results with minimal configuration.

{
  "input": {
    "prompt": "A sunset over mountains",
    "aspect_ratio": "16:9"
  }
}

Standard schema (8–12 parameters)

Models like TrueFusion Pro, TrueFusion Edge, and Flux.1 Edge add control over generation quality: num_inference_steps, guidance, seed, output_format, and output_quality. You get fine-grained tuning without overwhelming options.

{
  "input": {
    "prompt": "A cyberpunk cityscape at night",
    "aspect_ratio": "21:9",
    "num_inference_steps": 35,
    "guidance": 5,
    "seed": 42,
    "output_format": "png",
    "output_quality": 95
  }
}

Advanced schema (12+ parameters)

Models like TrueFusion Standard (with LoRA support), TrueFusion Ultra (with inpainting + style references), and Flux 2 Flex (with 10 reference images + prompt upsampling) expose the full range of creative control.

{
  "input": {
    "prompt": "Portrait in the style of @ref, soft lighting",
    "reference_images": ["https://example.com/style.jpg"],
    "reference_tags": ["ref"],
    "resolution": "1080p",
    "aspect_ratio": "4:3",
    "seed": 12345
  }
}

Output Schema Patterns

There are only two output patterns across all models:

Single URL

Most models return a single URL string:

{
  "type": "string",
  "format": "uri"
}

Response:

{
  "output": "https://delivery.skytells.ai/abc123.jpg"
}

Used by: TrueFusion Max, TrueFusion Ultra, TrueFusion 2.0, all video models, all audio models, Imagen, FLUX.2 Pro.

Array of URLs

Models that support multiple outputs return an array:

{
  "type": "array",
  "items": { "type": "string", "format": "uri" }
}

Response:

{
  "output": [
    "https://delivery.skytells.ai/abc123.jpg",
    "https://delivery.skytells.ai/def456.jpg"
  ]
}

Used by: TrueFusion, TrueFusion Pro, TrueFusion Edge, TrueFusion Standard, GPT-Image-1.


Type-Specific Schema Patterns

Image models

Common parameters: prompt, aspect_ratio, seed, output_format, output_quality

Advanced parameters vary by model:

  • img2img: image, prompt_strength
  • Inpainting: image, mask
  • Reference-based: reference_images, reference_tags, image_prompt, input_images
  • LoRA: lora_weights, lora_scale
  • Quality control: num_inference_steps, guidance, guidance_scale
  • Speed: go_fast, speed_mode, megapixels

Video models

Common parameters: prompt, aspect_ratio, duration/seconds

Model-specific patterns:

  • Frame control: start_image, end_image, last_frame
  • Reference: reference_images, input_reference
  • Audio: generate_audio (Veo), audio (Wan 2.5)
  • Flexibility: cfg_scale (lower = more creative)
  • Safety: negative_prompt, person_generation

Audio models

Unique parameters:

  • lyrics — song lyrics with structure tags ([Verse], [Chorus], etc.)
  • prompt — style/mood description
  • sample_rate, bitrate, audio_format — audio encoding settings

Pricing Models

Different models use different billing units. Understanding these helps you estimate costs accurately.

Pricing UnitHow it worksExample
Per imageFlat rate per generated imageTrueFusion: $0.03/image
Per secondBilled by output durationVeo 3.1: $0.43/second
Per predictionFlat rate per API callMera: $3.42/prediction
Per GPU secondBilled by GPU compute timeTrueFusion Pano: $0.02/GPU s
Per computing secondBilled by total compute timeTrueFusion Optima: $0.008/s
Per megapixelBilled by output resolutionFLUX.2 Pro: $0.02/MP
Per 5 secondsChunked video billingVideo Upscale: $0.10/5s

Some models have conditional pricing based on parameters — for example, Veo 3.1 Fast charges differently depending on whether generate_audio is enabled.


Partner Models

Some models are served through partner APIs (OpenAI, Google). These models have "inference_party": "partner" in their metadata and typically require you to provide your own API key:

{
  "input": {
    "openai_api_key": "sk-...",
    "prompt": "A watercolor painting of a cottage"
  }
}

Partner-served models: GPT-Image-1, Sora 2, Sora 2 Pro

The API key field uses "format": "password" and "x-cog-secret": true — it is never logged or stored by Skytells.

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