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ArtEmotion
Image

Fast Lightning SDXL

Credit-based pricing. Supports batch up to 4.

Fast Lightning SDXL preview
Output
image
Aspect ratio
1:1, 16:9, 9:16, 4:3, 3:4, Custom
Resolution
1024
Max batch
4

Inputs

  • Batch up to 4 per request

Example prompt

A majestic white tiger standing on top of a frozen waterfall during a snowstorm, piercing blue eyes, icy particles flying through the air, dramatic fantasy realism, ultra detailed fur and environment, cinematic composition
Try this prompt →
LLM-ready

API & LLM schema

Exact request contract for this model. Agents can fetch it from /api/v1/models?id=fal-ai/fast-lightning-sdxl.

POST/api/v1/generate23 fields · 2 required
FieldTypeRequirementContract
model_idconstantRequiredArtEmotion model identifier.
extraobjectOptionalModel-specific settings may also be nested here.
max_creditsnumberOptionalReject before submission if the estimated list price exceeds this cap. · Range: 1–…
webhook_urlstringOptionalFormat: uri
webhook_secretstringOptionalOptional model input.
folder_idstringOptionalOptional model input.
promptstringRequiredOptional model input.
num_inference_stepsnumberOptionalThe number of inference steps to perform. · Allowed: 1, 2, 4, 8 · Default: 4
expand_promptbooleanOptionalIf set to true, the prompt will be expanded with additional prompts. · Default: false
seedintegerOptionalThe same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.
safety_checker_versionstringOptionalThe version of the safety checker to use. v1 is the default CompVis safety checker. v2 uses a custom ViT model. · Allowed: v1, v2 · Default: v1
formatstringOptionalThe format of the generated image. · Allowed: jpeg, png · Default: jpeg
enable_safety_checkerbooleanOptionalIf set to true, the safety checker will be enabled. · Default: true
embedding_pathstringOptionalURL or Hugging Face path to textual-inversion embedding weights.
embedding_tokensarray<string>OptionalTokens that trigger the embedding when used in your prompt.
embedding_path_2stringOptionalURL or Hugging Face path to a second embedding.
embedding_tokens_2array<string>OptionalTokens for the second embedding.
embedding_path_3stringOptionalURL or Hugging Face path to a third embedding.
embedding_tokens_3array<string>OptionalTokens for the third embedding.
aspect_ratiostringOptionalAllowed: 1:1, 16:9, 9:16, 4:3, 3:4, Custom
resolutionstringOptionalAllowed: 1024
output_formatstringOptionalAllowed: png, jpeg
num_imagesintegerOptionalRange: 1–4
Minimal request example
{
  "model_id": "fal-ai/fast-lightning-sdxl",
  "prompt": "A majestic white tiger standing on top of a frozen waterfall during a snowstorm, piercing blue eyes, icy particles flying through the air, dramatic fantasy realism, ultra detailed fur and environment, cinematic composition"
}
Raw JSON Schema
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://www.artemotion.ai/api/v1/models?id=fal-ai%2Ffast-lightning-sdxl",
  "title": "Fast Lightning SDXL generation request",
  "description": "Request body accepted by POST /api/v1/generate for fal-ai/fast-lightning-sdxl.",
  "type": "object",
  "properties": {
    "model_id": {
      "type": "string",
      "const": "fal-ai/fast-lightning-sdxl",
      "description": "ArtEmotion model identifier."
    },
    "extra": {
      "type": "object",
      "additionalProperties": true,
      "description": "Model-specific settings may also be nested here."
    },
    "max_credits": {
      "type": "number",
      "minimum": 1,
      "description": "Reject before submission if the estimated list price exceeds this cap."
    },
    "webhook_url": {
      "type": "string",
      "format": "uri",
      "maxLength": 2048
    },
    "webhook_secret": {
      "type": "string",
      "maxLength": 512
    },
    "folder_id": {
      "type": "string"
    },
    "prompt": {
      "type": "string"
    },
    "num_inference_steps": {
      "title": "Num Inference Steps",
      "description": "The number of inference steps to perform.",
      "default": "4",
      "type": "number",
      "enum": [
        1,
        2,
        4,
        8
      ]
    },
    "expand_prompt": {
      "title": "Expand Prompt",
      "description": "If set to true, the prompt will be expanded with additional prompts.",
      "default": false,
      "type": "boolean"
    },
    "seed": {
      "title": "Seed",
      "description": "The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.",
      "type": "integer"
    },
    "safety_checker_version": {
      "title": "Safety Checker Version",
      "description": "The version of the safety checker to use. v1 is the default CompVis safety checker. v2 uses a custom ViT model.",
      "default": "v1",
      "type": "string",
      "enum": [
        "v1",
        "v2"
      ]
    },
    "format": {
      "title": "Format",
      "description": "The format of the generated image.",
      "default": "jpeg",
      "type": "string",
      "enum": [
        "jpeg",
        "png"
      ]
    },
    "enable_safety_checker": {
      "title": "Enable Safety Checker",
      "description": "If set to true, the safety checker will be enabled.",
      "default": true,
      "type": "boolean"
    },
    "embedding_path": {
      "title": "Embedding Path",
      "description": "URL or Hugging Face path to textual-inversion embedding weights.",
      "type": "string"
    },
    "embedding_tokens": {
      "title": "Embedding Tokens",
      "description": "Tokens that trigger the embedding when used in your prompt.",
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "embedding_path_2": {
      "title": "Embedding Path 2",
      "description": "URL or Hugging Face path to a second embedding.",
      "type": "string"
    },
    "embedding_tokens_2": {
      "title": "Embedding Tokens 2",
      "description": "Tokens for the second embedding.",
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "embedding_path_3": {
      "title": "Embedding Path 3",
      "description": "URL or Hugging Face path to a third embedding.",
      "type": "string"
    },
    "embedding_tokens_3": {
      "title": "Embedding Tokens 3",
      "description": "Tokens for the third embedding.",
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "aspect_ratio": {
      "type": "string",
      "enum": [
        "1:1",
        "16:9",
        "9:16",
        "4:3",
        "3:4",
        "Custom"
      ]
    },
    "resolution": {
      "type": "string",
      "enum": [
        "1024"
      ]
    },
    "output_format": {
      "type": "string",
      "enum": [
        "png",
        "jpeg"
      ]
    },
    "num_images": {
      "type": "integer",
      "minimum": 1,
      "maximum": 4
    }
  },
  "required": [
    "model_id",
    "prompt"
  ],
  "additionalProperties": false
}

FAQ

How much does Fast Lightning SDXL cost on ArtEmotion?

Credit-based pricing. You pay in ArtEmotion credits — every plan and top-up converts USD to credits at a fixed rate.

Do I get my credits back if Fast Lightning SDXL fails?

Yes — failed generations are never charged. The credits are released back to your balance automatically.

Can I call Fast Lightning SDXL from the API?

Yes. Use POST /api/v1/generate with model_id: "fal-ai/fast-lightning-sdxl". See the API reference for the full schema.

Where are my generations stored?

Every output is saved to your personal Library. You can export or delete everything any time from Privacy & deletion.

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