To generate an image at render time, have your application request it from an image-generation API when the user or feature needs it, show a pending state while generation runs, and display the returned image when it is ready. Do not make every page render trigger a fresh generation: reuse an existing result when appropriate, and design for delays, moderation blocks, and failed requests.
What “generate at render time” means
It means the application creates or requests an image during a user interaction or page workflow rather than relying only on an image prepared in advance. A user might ask for a product illustration, or a page may need a personalized visual that does not exist until the application has the relevant prompt or context.
The render itself should not be treated as a guarantee of an immediate image. Image generation is an asynchronous-feeling operation even when the API call is synchronous from the code’s perspective: the application waits for the provider to process the request, and complex prompts may take up to two minutes, according to OpenAI’s image-generation guide. The interface therefore needs a meaningful pending state and a plan for completion, failure, or cancellation.
Keep the generation request on application infrastructure rather than exposing a secret API key in browser code. Your server or trusted backend can validate the request, call the chosen API, apply your own access and cost controls, and return an image or a reference to one. The exact framework, job queue, storage service, and caching strategy are implementation choices; the API documentation does not prescribe them.
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Choose the API shape for the interaction
Use the Image API for a single image task
For a direct prompt-to-image request or an image edit, OpenAI recommends its Image API. This is a natural fit for a feature with a clear request and a single result, such as “create a hero illustration for this brief.” The API returns image data encoded as base64, which your application must decode before displaying or storing it.
Use the Responses API when image generation is part of a conversation
For a conversational experience or a multi-step workflow, OpenAI recommends the Responses API with its image-generation tool. The tool can generate a new image or edit image inputs in the conversation context. This structure is useful when the image request follows earlier turns, the user iterates on a result, or generation is one step in a broader assistant interaction. See the OpenAI image-generation guide for current endpoint behavior and parameters.
These choices are about workflow, not a universal quality ranking. A one-shot image feature does not need conversation machinery; a conversational editing experience may need the context and tool behavior of Responses. In either case, the interface should handle the returned final result explicitly.
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Build the render flow
- Collect and validate the request. Use a user prompt or a page-specific prompt assembled from trusted application data. Set reasonable limits on prompt length and allowed inputs before spending time or tokens on generation.
- Choose the API pattern. Use the Image API for one prompt-to-image generation or edit; use the Responses API when generation belongs in a conversation or multi-step task.
- Show a pending state immediately. Keep the surrounding page usable and explain that the image is being created. Do not leave an empty image box or make the whole page appear broken while the request runs.
- Call the API from trusted infrastructure. Keep credentials out of client-delivered JavaScript. Record enough request context to diagnose errors without unnecessarily logging sensitive prompt content.
- Decode and handle the result. The Image API returns base64 image data. Decode it into the representation your application expects, such as bytes for storage or a data URL for a short-lived preview. Validate that a usable final image was returned.
- Make the asset available to the interface. You can return the image data directly, or store the asset and return a URL or identifier. Choose based on your app’s payload size, persistence, access-control, and reuse needs; these are architectural decisions rather than requirements imposed by the API.
- Render accessibly. Provide useful alternative text when the image conveys content, and avoid using the prompt itself as alt text unless it accurately describes the resulting image. Preserve a retry or recovery path if generation fails.
Show progress without confusing previews with the final image
Both the Image API and the Responses API support streaming image generation. The official guide allows requesting zero to three partial images; fewer may arrive than requested if the final generation completes quickly. Partial images can give earlier visual feedback, but they are previews, not a promise that the completed image is already available.
The streaming reference describes server-sent events, including an image_generation.partial_image event whose payload includes base64 image data, a partial index, output format, quality, and size fields. If you implement streaming, your event-reading path should recognize partial events, show them as provisional, and replace or finalize the preview when the completed output arrives. Also handle a stream that produces no partials before completion. See the streaming event reference for the event structure.
- Keep a clear loading indicator until the final result is ready.
- Do not announce that generation is complete merely because a partial image arrived.
- On a stream error or disconnect, show a recoverable state instead of leaving a stale preview as if it were final.
- Offer partial previews only when earlier visual feedback improves the interaction enough to justify the added event-handling complexity.
Choose image format, size, and quality deliberately
The Image API defaults to PNG and also supports JPEG and WebP. OpenAI’s guide says JPEG is faster than PNG, which can help when latency matters; the right format still depends on image content, transparency needs, and delivery size. Do not select a format solely on generation speed if the result needs transparency or if downstream delivery requirements differ.
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The newer GPT Image 2.5 models support output size, quality, format, compression, and background controls. The guide lists recommended dimensions of 1024×1024, 1536×1024, and 1024×1536. Custom dimensions are subject to constraints on edge multiples, aspect ratio, and total pixel count, so verify current limits in the guide before using a custom size.
Higher quality and larger dimensions generally use more image tokens and can increase both latency and eventual cost. When comparing settings, consider expected wait, detail requirements, target aspect ratio, resulting payload and delivery cost, and whether partial previews improve the product experience. Avoid generating the largest output by default if the interface only needs a small thumbnail.
Plan for time, usage, and cost
OpenAI says complex prompts may take up to two minutes to process. That is long enough that a synchronous image request should not block an essential page load unless that delay is acceptable for the feature. For workflows where users can leave or navigate away, consider making the generation a distinct job and updating the interface when it completes; that is an application design choice, not a required OpenAI deployment pattern.
As listed in OpenAI’s guide checked September 29, 2026, GPT Image 2.5 token rates are:
| Token category | Rate in the guide | Qualification |
|---|---|---|
| Image input | $8 per million tokens | Token rate, not a fixed per-image charge |
| Cached image input | $2 per million tokens | Cached input pricing applies to the image-generation tool in Responses API, not direct Images API requests |
| Image output | $30 per million tokens | Actual usage varies with model and quality |
| Text input | $5 per million tokens | Token rate, not a fixed per-image charge |
| Cached text input | $1.25 per million tokens | Actual eligibility and consumption depend on the request |
Responses API requests can also include usage for the mainline model. Identical token rates do not imply identical cost per image: the model, selected quality, and token consumption affect the total. Inspect response usage and consult the cost calculator linked from the guide when estimating your workload.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Handle moderation and API errors safely
OpenAI filters both prompts and generated images under its content policy. The image-generation moderation option defaults to auto; low is described as less restrictive. A blocked request can identify whether input or output moderation was involved and may include coarse categories. Keep the end-user message straightforward and use available detail in developer logs, support workflows, or analytics rather than exposing confusing internal classifications.
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The separate Moderation API can classify text and/or image inputs when your application needs its own moderation signal. It does not replace the image-generation service’s own policy filtering. See the Moderation API guide and Moderations API reference.
- Transient rate limit or server failure: retry with backoff rather than immediately repeating the request in a tight loop.
- Quota or billing-related error: do not retry automatically; resolve the account or quota issue first.
- User-correctable generation error: show a useful prompt to revise the request, then retry only after the request changes.
- Moderation block: do not repeatedly resubmit the same blocked request. Offer a neutral explanation and a path to adjust the prompt if appropriate.
- Unexpected failure: inspect the HTTP status or SDK exception type, log the request ID, and consult OpenAI’s error guidance. Avoid logging secrets.
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ScreenshotNeo is a website screenshot API, not an AI image-generation API. It cannot create an illustration from a prompt; it can capture a webpage after your app has rendered an image or other content. If your goal is to capture the rendered page rather than generate its artwork, one GET request returns a screenshot or PDF. See the ScreenshotNeo API documentation.
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webp
Cookie banners, popups, and chat widgets are removed before the shot; bot checks, blank pages, and failed loads are never billed. An MCP server lets AI agents take screenshots, and 1,000 screenshots a month are free with no card; paid plans start at $5 for 3,000. Learn about ScreenshotNeo, or sign up free for 1,000 screenshots a month with no card.
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Frequently Asked Questions
Can I make image generation happen automatically whenever someone opens a page?
You can, but it is usually better to trigger it only when the image is genuinely needed and reuse an existing result when the same request can be served again. Otherwise page visits can create unnecessary waiting and usage.
Does streaming guarantee that a preview appears before the completed image?
No. A request can return fewer partials than requested, including none, if generation completes quickly.
Can the Moderation API replace image-generation moderation?
No. It can provide a separate classification signal for your workflow, while image-generation requests and outputs remain subject to the generation service’s policy filtering.
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