python/resources/images/methods/generate/index.md 2026-05-05 23:00 UTC to 2026-05-07 21:57 UTC

Create image

images.generate(ImageGenerateParams**kwargs) -> ImagesResponse

post /images/generations

Creates an image given a prompt. Learn more.

Parameters

• prompt: str

  A text description of the desired image(s). The maximum length is 32000 characters for the GPT image models, 1000 characters for dall-e-2 and 4000 characters for dall-e-3.

• background: Optional[Literal["transparent", "opaque", "auto"]]

  Allows to set transparency for the background of the generated image(s). This parameter is only supported for GPT image models that support transparent backgrounds. Must be one of transparent, opaque, or auto (default value). When auto is used, the model will automatically determine the best background for the image.

  gpt-image-2 and gpt-image-2-2026-04-21 do not support transparent backgrounds. Requests with background set to transparent will return an error for these models; use opaque or auto instead.

  If transparent, the output format needs to support transparency, so it should be set to either png (default value) or webp.

  • "transparent"

  • "opaque"

  • "auto"

• model: Optional[Union[str, ImageModel, null]]

  The model to use for image generation. One of dall-e-2, dall-e-3, or a GPT image model (gpt-image-1, gpt-image-1-mini, gpt-image-1.5, gpt-image-2, or gpt-image-2-2026-04-21). Defaults to dall-e-2 unless a parameter specific to the GPT image models is used.

  • str

  • Literal["gpt-image-1", "gpt-image-1-mini", "gpt-image-2", 5 more]

    • "gpt-image-1"

    • "gpt-image-1-mini"

    • "gpt-image-2"

    • "gpt-image-2-2026-04-21"

    • "gpt-image-1.5"

    • "chatgpt-image-latest"

    • "dall-e-2"

    • "dall-e-3"

• moderation: Optional[Literal["low", "auto"]]

  Control the content-moderation level for images generated by the GPT image models. Must be either low for less restrictive filtering or auto (default value).

  • "low"

  • "auto"

• n: Optional[int]

  The number of images to generate. Must be between 1 and 10. For dall-e-3, only n=1 is supported.

• output_compression: Optional[int]

  The compression level (0-100%) for the generated images. This parameter is only supported for the GPT image models with the webp or jpeg output formats, and defaults to 100.

• output_format: Optional[Literal["png", "jpeg", "webp"]]

  The format in which the generated images are returned. This parameter is only supported for the GPT image models. Must be one of png, jpeg, or webp.

  • "png"

  • "jpeg"

  • "webp"

• partial_images: Optional[int]

  The number of partial images to generate. This parameter is used for streaming responses that return partial images. Value must be between 0 and 3. When set to 0, the response will be a single image sent in one streaming event.

  Note that the final image may be sent before the full number of partial images are generated if the full image is generated more quickly.

• quality: Optional[Literal["standard", "hd", "low", 3 more]]

  The quality of the image that will be generated.

  • auto (default value) will automatically select the best quality for the given model.

  • high, medium and low are supported for the GPT image models.

  • hd and standard are supported for dall-e-3.

  • standard is the only option for dall-e-2.

  • "standard"

  • "hd"

  • "low"

  • "medium"

  • "high"

  • "auto"

• response_format: Optional[Literal["url", "b64_json"]]

  The format in which generated images with dall-e-2 and dall-e-3 are returned. Must be one of url or b64_json. URLs are only valid for 60 minutes after the image has been generated. This parameter isn't supported for the GPT image models, which always return base64-encoded images.

  • "url"

  • "b64_json"

• size: Optional[Union[str, Literal["auto", "1024x1024", "1536x1024", 5 more], null]]

  The size of the generated images. For gpt-image-2 and gpt-image-2-2026-04-21, arbitrary resolutions are supported as WIDTHxHEIGHT strings, for example 1536x864. Width and height must both be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1. Resolutions above 2560x1440 are experimental, and the maximum supported resolution is 3840x2160. The requested size must also satisfy the model's current pixel and edge limits. The standard sizes 1024x1024, 1536x1024, and 1024x1536 are supported by the GPT image models; auto is supported for models that allow automatic sizing. For dall-e-2, use one of 256x256, 512x512, or 1024x1024. For dall-e-3, use one of 1024x1024, 1792x1024, or 1024x1792.

  • str

  • Literal["auto", "1024x1024", "1536x1024", 5 more]

    The size of the generated images. For gpt-image-2 and gpt-image-2-2026-04-21, arbitrary resolutions are supported as WIDTHxHEIGHT strings, for example 1536x864. Width and height must both be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1. Resolutions above 2560x1440 are experimental, and the maximum supported resolution is 3840x2160. The requested size must also satisfy the model's current pixel and edge limits. The standard sizes 1024x1024, 1536x1024, and 1024x1536 are supported by the GPT image models; auto is supported for models that allow automatic sizing. For dall-e-2, use one of 256x256, 512x512, or 1024x1024. For dall-e-3, use one of 1024x1024, 1792x1024, or 1024x1792.

    • "auto"

    • "1024x1024"

    • "1536x1024"

    • "1024x1536"

    • "256x256"

    • "512x512"

    • "1792x1024"

    • "1024x1792"

• stream: Optional[Literal[false]]

  Generate the image in streaming mode. Defaults to false. See the Image generation guide for more information. This parameter is only supported for the GPT image models.

  • false

• style: Optional[Literal["vivid", "natural"]]

  The style of the generated images. This parameter is only supported for dall-e-3. Must be one of vivid or natural. Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images.

  • "vivid"

  • "natural"

• user: Optional[str]

  A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.

Returns

• class ImagesResponse: …

  The response from the image generation endpoint.

  • created: int

    The Unix timestamp (in seconds) of when the image was created.

  • background: Optional[Literal["transparent", "opaque"]]

    The background parameter used for the image generation. Either transparent or opaque.

    • "transparent"

    • "opaque"

  • data: Optional[List[Image]]

    The list of generated images.

    • b64_json: Optional[str]

      The base64-encoded JSON of the generated image. Returned by default for the GPT image models, and only present if response_format is set to b64_json for dall-e-2 and dall-e-3.

    • revised_prompt: Optional[str]

      For dall-e-3 only, the revised prompt that was used to generate the image.

    • url: Optional[str]

      When using dall-e-2 or dall-e-3, the URL of the generated image if response_format is set to url (default value). Unsupported for the GPT image models.

  • output_format: Optional[Literal["png", "webp", "jpeg"]]

    The output format of the image generation. Either png, webp, or jpeg.

    • "png"

    • "webp"

    • "jpeg"

  • quality: Optional[Literal["low", "medium", "high"]]

    The quality of the image generated. Either low, medium, or high.

    • "low"

    • "medium"

    • "high"

  • size: Optional[Literal["1024x1024", "1024x1536", "1536x1024"]]

    The size of the image generated. Either 1024x1024, 1024x1536, or 1536x1024.

    • "1024x1024"

    • "1024x1536"

    • "1536x1024"

  • usage: Optional[Usage]

    For gpt-image-1 only, the token usage information for the image generation.

    • input_tokens: int

      The number of tokens (images and text) in the input prompt.

    • input_tokens_details: UsageInputTokensDetails

      The input tokens detailed information for the image generation.

      • image_tokens: int

        The number of image tokens in the input prompt.

      • text_tokens: int

        The number of text tokens in the input prompt.

    • output_tokens: int

      The number of output tokens generated by the model.

    • total_tokens: int

      The total number of tokens (images and text) used for the image generation.

    • output_tokens_details: Optional[UsageOutputTokensDetails]

      The output token details for the image generation.

      • image_tokens: int

        The number of image output tokens generated by the model.

      • text_tokens: int

        The number of text output tokens generated by the model.

Example

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
)
for image in client.images.generate(
    prompt="A cute baby sea otter",
):
  print(image)

Response

{
  "created": 0,
  "background": "transparent",
  "data": [
    {
      "b64_json": "b64_json",
      "revised_prompt": "revised_prompt",
      "url": "https://example.com"
    }
  ],
  "output_format": "png",
  "quality": "low",
  "size": "1024x1024",
  "usage": {
    "input_tokens": 0,
    "input_tokens_details": {
      "image_tokens": 0,
      "text_tokens": 0
    },
    "output_tokens": 0,
    "total_tokens": 0,
    "output_tokens_details": {
      "image_tokens": 0,
      "text_tokens": 0
    }
  }
}

Generate image

import base64
from openai import OpenAI
client = OpenAI()

img = client.images.generate(
    model="gpt-image-1.5",
    prompt="A cute baby sea otter",
    n=1,
    size="1024x1024"
)

image_bytes = base64.b64decode(img.data[0].b64_json)
with open("output.png", "wb") as f:
    f.write(image_bytes)

Response

{
  "created": 1713833628,
  "data": [
    {
      "b64_json": "..."
    }
  ],
  "usage": {
    "total_tokens": 100,
    "input_tokens": 50,
    "output_tokens": 50,
    "input_tokens_details": {
      "text_tokens": 10,
      "image_tokens": 40
    }
  }
}

Streaming

from openai import OpenAI

client = OpenAI()

stream = client.images.generate(
    model="gpt-image-1.5",
    prompt="A cute baby sea otter",
    n=1,
    size="1024x1024",
    stream=True
)

for event in stream:
    print(event)

Response

event: image_generation.partial_image
data: {"type":"image_generation.partial_image","b64_json":"...","partial_image_index":0}

event: image_generation.completed
data: {"type":"image_generation.completed","b64_json":"...","usage":{"total_tokens":100,"input_tokens":50,"output_tokens":50,"input_tokens_details":{"text_tokens":10,"image_tokens":40}}}