DALL-E 2
What is DALL-E 2?
DALL-E 2 is OpenAI's second AI image model, producing sharper, higher-resolution images than its predecessor and adding the ability to edit, extend, and create variations of existing images.
At a glance
- Type of model
- Text-to-image diffusion model with inpainting and outpainting capabilities
- Developed by
- OpenAI
- Key capability
- Generating 1024x1024 images from text prompts with improved quality, plus inpainting, outpainting, and image variation generation
- How it fits in AI workflow
- Used for text-to-image generation, image editing, content extension, and variation exploration in creative and production workflows; succeeded by DALL-E 3 for most current professional applications
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How it compares
Compared with related concepts
DALL-E 2 vs Stable Diffusion 1. x: Both were released in 2022 and represent roughly contemporary capabilities in text-to-image generation. DALL-E 2 is proprietary, requires API access, and includes built-in safety filters with no local deployment option. Stable Diffusion is open-source, can be run locally, and supports extensive community customization through fine-tuning and extensions, but requires more technical setup. DALL-E 2 prioritizes safety and accessibility; Stable Diffusion prioritizes openness and flexibility.
Pro tip
DALL-E 2's inpainting and outpainting capabilities remain useful for specific editing tasks even as newer generation models surpass it in raw image quality. When you need to extend an existing image or replace a specific region with AI-generated content that matches the surrounding style, these editing modes can be more controllable than attempting the same task through prompt engineering alone in a generation-only workflow.
Types and variations
- Text-to-image generation produces new images from written prompts.
- Inpainting selects a masked region of an existing image and generates new content to fill it based on a text description.
- Outpainting extends the image beyond its original edges, generating coherent new content that matches the surrounding style and context.
- Image variations generate alternative versions of an uploaded image in the style of the original without a text prompt.
- Each mode uses the same underlying model but with different conditioning inputs and generation objectives.
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Try MorphicCommon use cases
- Generating concept images for design projects, marketing campaigns, and content creation workflows.
- Using inpainting to remove unwanted elements from photographs or replace them with AI-generated alternatives.
- Extending illustrations or photographs beyond their original borders using outpainting to create wider compositions.
- Generating style-consistent variations of existing imagery for A/B testing or creative exploration.
- Integrating with development workflows via OpenAI's API to embed image generation capability in custom applications.
Ready to create?
Direct scenes, design characters, and ship full films
All-in-one AI creative platform with simple, transparent pricing, no speed throttles, and an infinite Canvas for max creativity.