Explore GPT-Image 2 through Text to Image, Image Edit workflows in one page, then move directly into the shared Creator workbench to generate, compare, and continue production.
This version keeps the story tight for paid traffic: show the model, show the two core workflows, then let the visitor try it before momentum drops.
Put Text to Image and Image Edit on one conversion-focused model page, so paid traffic does not have to guess which tool family to click first.
Keep the live Creator workbench above the fold, so the first interaction already feels like product use instead of a brochure read.
Shift the proof toward ad-ready outputs, UI concepts, product visuals, and polished revisions instead of text-heavy language-specific examples.
This page is organised around GPT-Image 2's role in prompt-led concept exploration, so users can understand where it fits before moving straight into creation.
Start by switching between the core GPT-Image 2 workflows so the page lands on the mode that matches your current intent.
Use the right mix of prompt, references, or existing assets based on what the current GPT-Image 2 mode expects.
Iterate inside the workbench, compare competing GPT-Image 2 directions, and keep the strongest output moving forward.
Once you find a strong direction, move into Creator with the same context instead of rebuilding the workflow from scratch.
Visitors should understand both routes at a glance: start from scratch with Text to Image or tighten an existing asset with Image Edit, then move directly into the shared workbench.
Use GPT-Image 2 when you need ad visuals, UI concepts, product hero shots, or polished stills from short natural prompts.
Switch into Image Edit when the job is to clean up layouts, retouch photoreal assets, restyle screenshots, or tighten an existing visual direction.
This section helps users judge whether GPT-Image 2 should lead the prompt-led concept exploration work or support a later early exploration step in production.
Use GPT-Image 2 when you need ad visuals, UI concepts, product hero shots, or polished stills from short natural prompts.
Use GPT-Image 2 when you need ad visuals, UI concepts, product hero shots, or polished stills from short natural prompts.
Switch into Image Edit when the job is to clean up layouts, retouch photoreal assets, restyle screenshots, or tighten an existing visual direction.
Switch into Image Edit when the job is to clean up layouts, retouch photoreal assets, restyle screenshots, or tighten an existing visual direction.
The examples below stay focused on commercially legible directions: polished portraits, structured layouts, branded concepts, and clean mascot-style assets.
The most persuasive proof is seeing GPT-Image 2 produce usable outputs fast, not reading another generic model summary.
Put Text to Image and Image Edit on one conversion-focused model page, so paid traffic does not have to guess which tool family to click first.
Keep the live Creator workbench above the fold, so the first interaction already feels like product use instead of a brochure read.
Shift the proof toward ad-ready outputs, UI concepts, product visuals, and polished revisions instead of text-heavy language-specific examples.

Use short prompts to land polished, camera-aware portraits that already feel close to campaign-ready output.

Structured grids, repeated character identity, and clean panel logic make GPT-Image 2 useful for profile systems and concept boards.

Move from idea to visual direction fast with sketch-like concept treatments that still feel intentional and presentation-ready.

Simple product mascots, icons, and friendly branded characters come out crisp enough for landing pages, onboarding, and app surfaces.
The FAQ stays specific to what GPT-Image 2 is meant to do inside OpenAI, why it suits early exploration, and how it connects to the shared Creator workbench.