DALL·E 3 is OpenAI's text-to-image model, focused on transforming subjects, scenes, and detailed relationships in natural language into images. Compared with DALL·E 2, it places greater emphasis on accurately understanding the same description, making it suitable for developing creative briefs into illustrations, poster concepts, and marketing visual drafts. On this platform, you can submit prompts through the image generation entry point and obtain image results.
Clarify capacity, inputs and outputs, and invocation methods before selecting a model.
Text-to-image generation is the model's native purpose; editing, result packaging, and asynchronous tasks are invocation methods provided by this platform and do not mean that all shared image parameters apply to this model.
Learn what dall-e-3 can bring to your work.
DALL·E 3 focuses not only on capturing the subject in a prompt, but also on more carefully understanding the details in the description. When creating, you can write the subject, environment, actions, and compositional relationships as complete sentences, making the text brief the basis for organizing the image. It is suited to image-generation tasks that need to express clear intent rather than simply obtain random inspiration.
A prompt can begin with a creative idea, then add the scene, materials, lighting, and mood. DALL·E 3 is designed to value natural-language expression, reducing reliance on special prompting techniques. For projects that need to explore visual directions, you can retain the core theme, revise key descriptions, and gradually form concept proposals for discussion.
Generated results can be retrieved through a URL or provided as b64_json for an application to process; responses may also include revised_prompt, making it easier to understand the description actually used. When task-based processing is needed, asynchronous returns and callbacks can be used to connect image creation to content-production workflows, without placing every operation in an interactive interface.
Start with specific tasks to find where the model can be effective.
Enter the campaign theme, target atmosphere, subject placement, and background requirements to generate key-visual drafts for discussion. For example, write product arrangement, lighting direction, and intended negative space into the prompt, then explore options around different descriptions. The deliverables are suitable as material for creative reviews, while final brand elements and layout can continue to be completed by designers.
Break a story segment into character actions, environment, and image mood, then submit a complete scene description to generate illustrations or scene concepts. It is suitable for helping authors, editors, and artists communicate the visual intent in text. When dealing with sequential images, each scene should be described separately, and characters and environments should be manually checked against project requirements.
Rewrite abstract ideas as visible subjects, spatial relationships, and visual styles to obtain image concepts that teams can discuss easily. This can be used to verify whether a brief is clear enough and to compare different compositional approaches. The focus is on using generated images to identify descriptions that need to be added, then organizing them into clearer design tasks and delivery requirements.
Choose based on task complexity, input materials, and expected results.
If the task depends on a relatively complete written brief and you want the image to more closely match the details in the description, DALL·E 3 is a higher-priority choice than DALL·E 2. OpenAI explicitly states that it has significant improvements with the same prompt, but this does not mean every object and spatial relationship can be rendered accurately in a single attempt; results should still be selected according to creative requirements.
When conceiving a new image from text, you can choose DALL·E 3; if the project primarily relies on masked local edits, multiple reference images, or strictly preserving details of the original image, prioritize evaluating GPT Image models that explicitly support these operations. DALL·E 3's image editing endpoint can accept images and instructions, but it should not be treated as a pixel-level retouching tool when planning deliverables.
From a small-scale task to formal integration.
Define the goal, required inputs, and output requirements, using real business examples as a starting point.
Open the playground page, confirm the parameters supported by this endpoint, then submit a small-scale task to review the results.
Keep the complete model ID, use the request format specified in the documentation, and confirm billing rules on the Pricing page.
Understand output quality and capability scope before formal use.
Answers to common questions about using dall-e-3.
The main difference is its understanding of textual details and creative intent. OpenAI explicitly states that DALL·E 3 offers significant improvements even when using the same prompt. For briefs containing descriptions of subjects, environments, and relationships, it is better suited as the model to try first, though you should still review the actual image.
Start by describing the main subject, then add actions, environment, composition, lighting, and style, expressing key relationships in clear sentences. You can gradually expand from a short idea rather than stacking large numbers of tags. When revising a concept, keep the core description and adjust the parts that need to change to make results easier to compare.
Multi-turn discussion is not automatically enabled. Creative collaboration between DALL·E 3 and ChatGPT is a product workflow; image generation requests require submitting a prompt and model. If you want to discuss composition or refine an idea first, organize the text before using the resulting description to generate an image.
This platform provides an image modification option for dall-e-3, where you can submit an image URL and a modification description. Clearly state what you want to change and what you want to preserve; this differs from the model's native text-to-image positioning, so you should not assume it supports masking or strictly faithful editing.
OpenAI states that images created with DALL·E 3 may be reprinted, sold, or made into merchandise without seeking separate permission from OpenAI. This does not replace your project's own rights review; if an image involves brands, people, or existing works, you should still check the relevant permissions and terms of use before commercial publication.
Model information · Updated: 2026-10-01. See the API and pricing sections for call parameters and billing rules.
Start with a clear goal and assess from actual results whether it suits your work.
Pricing
$0.019–$0.0571· per generation
You pay$13,584for 142,800 credits · $0.0951 / credits46% OFF
You're billed in credits. Pick a top-up tier to see its per-credit rate — the larger the top-up, the cheaper each credit.
This is only a basic call example. See the full docs for more parameters and advanced usage.
View Docs