GPT Image 2
English
Built around public GPT Image capabilities: generation, editing, and output control

GPT Image 2 AI image generator for prompts, edits, and transparent assets

GPT Image 2 is organized around publicly documented GPT Image workflows for teams that need faster visual production.
Generate images from prompts, edit with references or masks, and export the right size, quality, format, or transparent background for real delivery work.

Open StudioView Pricing

Best fit for ad creatives, product mockups, landing page visuals, thumbnails, and transparent PNG assets.

introduce

What you can do with GPT Image 2

GPT Image 2 is clearest when presented as four practical image workflows: generate from text, create from references, edit locally with a mask, and export the right format for delivery.

Text-to-image generation

Turn prompts into campaign concepts, blog covers, social visuals, and first-pass product scenes without waiting on a full design cycle.

Reference-driven creation

Use one or more input images to build a new image around products, packaging, materials, or composition cues.

Masked edits and refinements

Change only part of an image when the background, prop, surface, or text area needs revision instead of regenerating everything.

Delivery-ready output settings

Choose square, landscape, or portrait output, adjust quality, set PNG, JPEG, or WebP, and enable transparency when the asset must fit real layouts.

Why teams use GPT Image 2 for real image work

Users care less about abstract benchmark claims and more about whether the workflow is usable, controllable, and fit for real delivery needs.

benefits

Better instruction following and text rendering

Official GPT Image guidance positions the model family above DALL·E for instruction following, text rendering, detailed editing, and real-world knowledge, which makes it more useful for posters, covers, UI concepts, and branded visuals.

benefits

Higher-fidelity reference editing

GPT Image supports multiple input images and high input fidelity, which helps preserve products, faces, logos, and other critical details during revisions.

benefits

More control at export time

Choose 1024x1024, 1536x1024, or 1024x1536 output, tune quality from low to high, switch file format, and enable transparency for PNG or WebP assets.

How GPT Image 2 fits a real image workflow

The clearest workflow is simple: generate, guide, edit, and export.

1

Start with the working prompt

Begin with the subject, scene, composition, and text requirements in plain language, then add style or lighting only when it improves the result.

2

Add references or a mask

Upload one or more reference images when products, logos, faces, or layout cues matter. Use a mask when only part of the image should change.

3

Set delivery options

Choose square, landscape, or portrait size, select quality level, pick PNG, JPEG, or WebP, and turn on transparent background when the asset needs layering.

4

Iterate before export

Refine the same direction across multiple edits, review text placement and composition, then export the approved asset for campaign, product, or content use.

Use Cases

Best-fit use cases for GPT Image 2

These use cases have clear prompt, editing, and export needs, which makes them the best fit for GPT Image 2 in real production work.

Ad creatives and social campaign visuals

Generate paid social images, hero sections, posters, and headline-led marketing concepts faster without waiting on a full design pass.

Blog covers and editorial visuals

Create thumbnails, featured images, and repeatable visual systems for editorial teams without scavenging stock libraries.

Product mockups and ecommerce graphics

Combine product references, packaging, and props into new scenes before your team commits to a full shoot or production design pass.

Transparent assets and UI graphics

Export stickers, icons, sprites, cut-outs, and layered PNG assets that can drop directly into websites, apps, and product pages.

Landing page and SaaS launch visuals

Produce onboarding graphics, feature callouts, and waitlist hero images with prompt-driven iteration instead of scattered briefs and tools.

Agency revisions and client-ready variants

Keep editing the same concept with references, masks, and output controls until the asset is ready for review, pitch, or delivery.

FAQ about GPT Image 2

If you need help with GPT Image 2 plans, supported workflows, or usage, contact [email protected].
GPT Image 2 is best understood as a workflow for text-to-image generation, reference-driven creation, masked edits, transparent backgrounds, and output controls for size, quality, and format.
Yes. You can use one or more reference images to drive a new result, and you can use a mask to guide local edits. The mask is prompt-guided, so it may not follow exact pixel boundaries every time.
Yes. You can export PNG, JPEG, or WebP. Transparent backgrounds are available with PNG and WebP, and they typically work best at medium or high quality.
Public examples support 1024x1024, 1536x1024, 1024x1536, and auto size selection, along with low, medium, high, and auto quality settings. Standard square output is usually the fastest.
It is fair to present text rendering as a strength. The official documentation says GPT Image improves on DALL·E here, but exact text placement and clarity can still require iterative prompting and manual review.
It can support consistency-oriented workflows, especially with references, but the official docs still note that recurring characters and brand elements may occasionally drift across generations.
Yes. Complex prompts can take longer to process, in some cases up to 2 minutes, and composition control, exact text placement, and cross-image consistency should still be reviewed before final delivery.

Start with the GPT Image 2 workflow that is already public

Open GPT Image 2 Studio to generate from text, guide results with references, edit only what changed, and export the format your team actually needs.

Open Studio