OpenAI DALL·E 3 for high-fidelity text-to-image generation available as a managed API on WaveSpeedAI. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.04per run·~25 / $1
ExamplesView all
A breathtaking aerial view shows a river winding like a dark ribbon through lush fields and hills, reflecting the soft pink-orange hues of sunrise or sunset in a serene, picturesque landscape.
A drone camera circles a historic church on a rocky outcrop along the Amalfi Coast, highlighting its stunning architecture, tiered patios, and the dramatic coastal views with waves crashing below and people enjoying the scene in the warm afternoon light.
A playful dog in a pink coat with a red leash dashes across a muddy field with sparse crops. The camera tracks its energetic movement from right to left against a backdrop of trees and distant power lines under an overcast sky. The realistic, medium shot captures a candid, lively moment in soft, diffused light.
A breathtaking aerial view shows a river winding like a dark ribbon through lush fields and hills, reflecting the soft pink-orange hues of sunrise or sunset in a serene, picturesque landscape.
A coastal landscape painting with a prominent archway is displayed on an easel in a bright studio. A camera pan reveals a table cluttered with art supplies and a potted plant, enhancing the artistic vibe. Large windows and soft natural lighting create a cozy, creative atmosphere.
A tomato surfing on a piece of lettuce down a waterfall of ranch dressing, with exaggerated surfing moves and creamy wave effects to highlight the 3D animated fun.
Chinese ancient style, realism. A young woman, dressed in an embroidered red qipao, walks along the ancient streets of a bustling Chinese town. The red lanterns hanging above her sway gently in the evening breeze, and her calm, confident stride contrasts with the lively atmosphere of merchants and performers around her.
A black-and-white film captures a pianist playing in an empty, decaying theater. His deft fingers and echoing music create a haunting ambiance as dust motes float in the faint light. The gleaming grand piano under the spotlight contrasts with the worn seats and peeling walls, evoking nostalgia.
A vibrant green parrot with hints of yellow and blue perches on a person’s lap, who is wearing grey pants. The parrot features a white beak, grey head, and a black eye. In the background, a red couch and a TV displaying a colorful video with “bilibili” text complete the scene.
A panda bear with distinct black patches climbs and rests on a wooden log platform amid lush, natural foliage.
A serene, mystical forest at dawn, soft golden sunlight filtering through towering ancient trees, glowing mist rising from the forest floor. A lone majestic white stag stands beside a crystal-clear pond, its antlers luminescent. Watercolor illustration, ethereal and inspirational mood, close-up perspective.
Related Models
README
OpenAI DALL·E 3
DALL·E 3 is OpenAI’s most advanced text-to-image system, capable of generating highly detailed, realistic, and creative visuals directly from natural language descriptions. It builds upon OpenAI’s extensive world knowledge and artistic training to create images that are accurate, expressive, and aligned with your intent.
🎨 Key Features
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Natural Language Understanding Converts descriptive prompts into coherent, visually rich images with impressive contextual accuracy.
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Flexible Visual Styles Supports multiple artistic directions — from photorealistic renderings to digital art, concept sketches, and more.
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Text Rendering Accurately incorporates text and signage into generated images for posters, packaging, and editorial design.
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Global Knowledge Integration Leverages OpenAI’s broad factual grounding to produce culturally and contextually accurate imagery.
🛡️ Safety & Reliability
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Built-in safety filters to prevent generation of unsafe or restricted content.
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Incorporates C2PA metadata for content authenticity and traceability.
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Optional moderation sensitivity parameter:
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auto(default) – Standard filtering -
low– Less restrictive filtering for research and artistic use
⚙️ Capabilities
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Input: Text prompt (supports natural language)
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Output: Static image
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Supported Styles: Photorealistic, digital painting, illustration, abstract, minimalist, cinematic, and more
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Supported Quality:
standard,hd -
Resolution Options:
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1024×1024 -
1024×1792 -
1792×1024
💰 Pricing
| Quality | Resolution | Price per Image (USD) |
|---|---|---|
| Standard | 1024×1024 | $0.040 |
| Standard | 1024×1792 / 1792×1024 | $0.080 |
| HD | 1024×1024 | $0.080 |
| HD | 1024×1792 / 1792×1024 | $0.120 |
💡 Best Use Cases
- Marketing & Branding — Generate ad-ready visuals and concept mockups effortlessly.
- Design & Illustration — Quickly iterate creative ideas and styles.
- Education & Media — Create visual assets for courses, articles, and storytelling.
- Content Creation — Produce social posts, thumbnails, and blog images with minimal effort.
📝 Notes
- For best results, use clear, focused prompts (e.g., “A cinematic portrait of a woman standing under neon lights in Tokyo”).
- All generations comply with OpenAI’s content and safety guidelines.
Dall E 3 API — Quick start
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/openai/dall-e-3 with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Dall E 3 below.
HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/openai/dall-e-3" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"quality": "standard",
"style": "vivid",
"enable_sync_mode": false,
"enable_base64_output": false
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].Node.js example
// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("openai/dall-e-3", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"quality": "standard",
"style": "vivid",
"enable_sync_mode": false,
"enable_base64_output": false
});
console.log(result.outputs[0]); // → URL of the generated outputPython example
# pip install wavespeed
import wavespeed
output = wavespeed.run(
"openai/dall-e-3",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"quality": "standard",
"style": "vivid",
"enable_sync_mode": false,
"enable_base64_output": false
}
)
print(output["outputs"][0]) # → URL of the generated outputDall E 3 API — Frequently asked questions
What is the Dall E 3 API?
Dall E 3 is a OpenAI model for image generation, exposed as a REST API on WaveSpeedAI. OpenAI DALL·E 3 for high-fidelity text-to-image generation available as a managed API on WaveSpeedAI. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
How do I call the Dall E 3 API?
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/openai/openai-dall-e-3.
How much does Dall E 3 cost per run?
Dall E 3 starts at $0.040 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
What inputs does Dall E 3 accept?
Key inputs: `prompt`, `size`, `enable_base64_output`, `enable_sync_mode`, `quality`, `style`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/openai/openai-dall-e-3.
How long does Dall E 3 take to generate?
Average end-to-end generation time on WaveSpeedAI is around 20 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Can I use Dall E 3 outputs commercially?
Commercial usage rights depend on the model's license, set by its provider (OpenAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.