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To generate one image and use it immediately in your application, call a direct image-generation endpoint, wait for its response, decode the returned image data, and save or return the resulting bytes. “Synchronous” describes that wait-and-return pattern; it does not mean the provider guarantees a fixed completion time. For a single prompt, OpenAI’s Image API is the direct workflow documented for this task. Use the Responses API when image generation belongs in a conversation or multi-step process instead.
What synchronous image generation means
A synchronous client sends a request and awaits its result before continuing. The result might contain image data directly, such as base64-encoded bytes, or a URL, depending on the provider, model, and endpoint. Your application then has to handle the response, convert or retrieve the image, and decide where to store or send it.
This is an application-flow description, not a speed promise. The reviewed provider documentation describes request and response formats, but does not establish a fixed response-time guarantee or a neutral, comparable latency figure across services. A long-running request can therefore still make a synchronous design unsuitable for a user-facing request that must return quickly.
Choose the right endpoint for the workflow
| Workflow | Best fit | Why |
|---|---|---|
| One prompt, one image-generation operation | OpenAI Image API | OpenAI’s guide recommends the Image API for generating or editing a single image from one prompt. |
| Image generation inside a conversation or a multi-step interaction | OpenAI Responses API with its image-generation tool | It supports conversational context, iterative edits, and image inputs as part of a broader interaction. |
| Google image generation using the documented Interactions example | Gemini API | The documented example creates an interaction and returns an output image as base64 data, with output-format controls. |
These are workflow distinctions, not a ranking of image quality, speed, or cost. Model identifiers, account eligibility, controls, and availability can change; check the chosen provider’s current documentation before deploying.
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Generate and save an image with OpenAI’s Image API
The Image API route is POST /images/generations. Its request includes a model and prompt; optional controls include image count, quality, size, output format, and other model-dependent settings. The following Python example shows the response-processing pattern. Install the OpenAI Python SDK and configure OPENAI_API_KEY using the current official setup guidance for your environment before running it.
from pathlib import Path
from openai import OpenAI
client = OpenAI()
result = client.images.generate(
model="gpt-image-1",
prompt="A small glass greenhouse on a rainy city rooftop at dusk, editorial illustration",
size="1024x1024",
quality="high",
n=1,
)
if not result.data:
raise RuntimeError("The image API returned no image data")
image_b64 = result.data[0].b64_json
if not image_b64:
raise RuntimeError("The response did not contain base64 image data")
import base64
image_bytes = base64.b64decode(image_b64)
Path("generated.png").write_bytes(image_bytes)The important sequence is the call, the empty-result check, base64 decoding, and writing binary bytes. Do not treat the returned base64 string as a ready-to-display image file. Decode it first, then persist or pass those bytes to the next stage of your application.
cURL request shape
The equivalent REST endpoint is POST /images/generations. Authenticate with an API key held outside source control. The precise fields accepted depend on the model and current API reference; this example requests one image and asks for PNG output.
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curl https://api.openai.com/v1/images/generations
-H "Authorization: Bearer $OPENAI_API_KEY"
-H "Content-Type: application/json"
-d '{
"model": "gpt-image-1",
"prompt": "A small glass greenhouse on a rainy city rooftop at dusk, editorial illustration",
"size": "1024x1024",
"quality": "high",
"n": 1,
"output_format": "png"
}'
-o response.jsonThis saves the JSON response, not a standalone PNG. For GPT Image, extract its base64 data from the response and decode it to a binary file, as in the Python example. Keep response parsing aligned with the current endpoint schema rather than assuming every image API returns an image URL.
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Decode the response and deliver the image
Base64 response data
OpenAI documents base64 image data for GPT Image, and Google’s documented Gemini example also exposes base64-encoded output image data. Base64 is a text representation of binary content: decode it before writing a file, returning an image response, or uploading it to object storage. Check that the expected image field exists first so an API error response is not accidentally treated as image content.
URL response data
Do not assume every provider or model returns base64. The OpenAI reference distinguishes GPT Image from DALL·E 2 and DALL·E 3: those DALL·E models can return either a URL or b64_json, and the documented returned URLs are valid for 60 minutes. A URL is not a permanent storage location; fetch and store the image promptly if your application needs it later. GPT Image does not support the response_format parameter and returns base64 data instead.
Save safely in production
- Write decoded data in binary mode, not text mode.
- Use a filename extension consistent with the requested output format.
- Validate the response before decoding and handle malformed base64 or provider errors.
- For web delivery, set a matching content type such as
image/pngorimage/webpwhen serving stored bytes. - Keep API credentials on your server. Do not expose a provider secret in browser code.
Choose generation options deliberately
Image count
OpenAI documents n as the number of images, defaulting to one in its guide. The reference gives a range of 1 to 10, while DALL·E 3 supports only one. Treat that range as endpoint documentation, not a promise that every model accepts every count.
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GPT Image output formats include PNG, JPEG, and WebP. Compression controls are available for JPEG or WebP. OpenAI’s guide says JPEG is faster than PNG and recommends it when latency is a concern; that is the provider’s guidance, not a cross-provider benchmark. Choose a format based on downstream compatibility and file-size needs.
Dimensions
The reference lists common GPT Image sizes of 1024×1024, 1536×1024, and 1024×1536. It also allows qualifying custom dimensions: width and height must be divisible by 16, and the aspect ratio must be between 1:3 and 3:1. Maximum edge and total pixel limits apply as well. Verify the current model-specific constraints before relying on custom dimensions.
Quality and model choices
Model and quality options are provider- and model-specific. A parameter accepted for one model may be rejected for another. Start with the documented model value and only add optional settings that the selected model supports; consult the live reference if a request returns a parameter validation error.
When to use the Responses API instead
Choose Responses when image generation is one action in a continuing interaction—for example, when a user asks for an image, reacts to it, then requests an edit informed by earlier messages or supplied images. OpenAI documents multi-turn editing and flexible image inputs in this workflow. The guide describes carrying image-generation outputs or IDs across turns and using previous_response_id to continue a response sequence.
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For a single direct generation, the Image API is the more direct fit. Responses can also stream partial images: the reference describes zero to three partial images for streaming requests. That is a separate strategy for receiving intermediate updates; it is not required when your application simply awaits the final image.
Google Gemini response pattern
Google’s documented example uses client.interactions.create with the gemini-3.1-flash-image model and a text input, then reads interaction.output_image.data, decodes the base64 value, and writes an image file. The docs also show response-format controls such as output type, aspect ratio, and image size. This describes that documentation example, not identical behavior or availability for every Gemini image model or account.
Whichever provider you use, keep generation and response handling separate in your application. One function should submit the prompt and supported options; another should validate the returned structure, decode or download the content, and return bytes or a storage reference. That separation makes it easier to change models without mixing provider-specific response fields into the rest of your application.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Reliability, latency, and cost considerations
A synchronous request is simplest when the caller can remain waiting until completion. It also ties the calling request or process to provider response time, which is not given as a fixed guarantee in the reviewed documentation. For an interactive product, set an appropriate client timeout, surface a useful pending or failure state, and decide whether a slower operation should move to a background job. Do not return a success response until you have verified that usable image data arrived.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchPrices change and depend on model and usage. OpenAI’s 2025 launch announcement gave historical prices for gpt-image-1—$5 per million text-input tokens, $10 per million image-input tokens, and $40 per million image-output tokens—and approximate launch-era square image costs of $0.02, $0.07, and $0.19 for low, medium, and high quality. These are historical announcement figures, not current rate guidance. Check the provider’s live pricing page and model documentation before estimating a budget.
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Likewise, OpenAI reported that 130 million users created 700 million images in ChatGPT during the first week after the feature’s 2025 introduction. Those are company-reported historical ChatGPT usage figures, not API demand, current totals, or evidence of API performance.
Troubleshoot common failures
- Authentication failure: confirm the server process can read the intended API key and that the request uses the provider’s required authentication header. Do not print secrets into logs.
- Unsupported parameter or size: compare every setting against the selected model’s current reference. Remove options unsupported by that model, and check custom dimensions against divisibility, aspect-ratio, and size limits.
- No image in the response: inspect the error/status payload before trying to decode. Check the documented response field for that exact provider and model; a URL-based result and a base64 result require different handling.
- Corrupt output file: ensure you decoded the base64 value rather than writing the text string, and ensure the filename extension and serving content type match the requested format.
- Request takes too long: no fixed completion time is established here. Choose a timeout appropriate to your application, communicate that generation is pending, and consider background processing if the caller should not wait.
- Access or verification block: some GPT Image usage may require API Organization Verification. Requirements can change, so check the current account guidance for the model you intend to use.
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ScreenshotNeo is a website screenshot API, not an image-generation model: it captures a rendered web page as an image or PDF. If your actual need is to turn a URL into a screenshot, one GET request returns the result. See the ScreenshotNeo API documentation for parameters and response details.
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webpCookie banners, newsletter popups, and chat widgets are removed before capture; bot checks, blank pages, and failed loads are never billed. ScreenshotNeo also has an MCP server so AI agents can take screenshots. The Free plan includes 1,000 screenshots a month with no card, and paid plans start at $5 for 3,000. Sign up for free and get 1,000 screenshots a month with no card.
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Does synchronous mean the image arrives instantly?
No. It means the application waits for the call to return; the reviewed documentation does not establish a fixed response time.
Can I use ScreenshotNeo to generate a new image from a prompt?
No. ScreenshotNeo captures rendered web pages. It is not an image-generation model.
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