OpenAI's image model that follows instructions like a copy editor. Photoreal portraits, sharp text, references, posters — the kind of stills that won't make you whisper "please render the words right this time."
Brief the lens, the time of day, the mood — GPT Image 2 renders skin tones, fabric weave and ambient bounce at fidelity that holds up to a hundred-percent crop. The frames feel scanned, not synthesized.
Stack constraints in a single sentence — three subjects in specified positions, a foreground prop, a particular palette — and the model honours all of them at once. No more re-prompting until something accidentally sticks.
Quote the copy, name the typeface, and the text lands crisp at small sizes. Latin, Chinese, Japanese, Korean, Cyrillic, Arabic — same model, same workflow. No after-the-fact relettering in Photoshop.
Drop in any image, describe what should change. The model rewrites only the requested region — lighting holds, composition holds, identity holds. Useful for product variants, brand consistency, and unblocking shots that almost worked.
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·03The same prompt vocabulary moves the model across photographic, cinematic, watercolour, anime, vector and pencil styles. No stylistic fine-tunes to swap, no separate checkpoints — describe the look and it lands.
No model picker, no provider key, no prompt engineering ritual. Describe the shot, the agent picks GPT Image 2 when it fits — and you stay in the conversation while it iterates.
Type the shot like you'd brief a photographer — lens, light, framing, mood. Drop in any reference image straight from your asset library if you want a face or a brand to stay on-model.
The agent picks GPT Image 2 the moment your prompt looks like a still — poster, character ref, style card, key art. No model picker, no provider key, no copy-paste.
"Make the title bigger, swap the hat for navy velvet, keep everything else." Surgical edits stay surgical — no full re-roll, no losing the parts you liked.
Square stills only — single rail, no decorative crops, no upscaled placeholders.
GPT Image 2 is great. Snaptale makes it directable — persistent assets, character locks, the studio and the agent all sharing one project.
Every character ref, product shot, brand mark you've ever uploaded is one @-mention away from the prompt. No drag-and-drop dance, no hunting through Finder.
Snaptale carries the same character/style anchor through every subsequent still and clip — even when you switch over to a video model later.
Targeted retouches stay in the conversation. No tab-hopping to a separate edit surface, no losing context between iterations.
Aspect, quality, output format — Snaptale picks sensible values per use case. You can override, but you almost never need to.
No. Snaptale routes your request and bills the credits — you don't bring a key, manage rate limits, or worry about which version is current.
GPT Image 2 itself doesn't render transparency. If you need a transparent PNG (logo cutout, sticker), Snaptale falls back to GPT Image 1.5 for that single render and stitches the result back into your project.
Multiple. The model treats them at high fidelity automatically — you don't tune a strength knob. Pass one to edit, or pass several to combine subjects, styles, or layouts.
Put the exact copy in “straight quotes” and describe the typography (“bold sans-serif, centered, high contrast”). Quoting is the single highest-leverage tip we know.
Yes — that's the workflow Snaptale is built around. Generate or upload a reference portrait once, lock it as a project asset, and every subsequent prompt that @-mentions it inherits the likeness.
The agent reads your intent. Static prompts stay on GPT Image 2; the moment you ask for motion ("a 5-second shot of..."), it routes to Seedance 2.0 (or Happy Horse 1.0 for real-people motion) and reuses your stills as first frames.