Try OpenAI's newest image model, gpt-image-2 (ChatGPT Images 2.0), online inside Genspark. Describe what you want and get clean typography, accurate infographics, and 4K-ready visuals — all in one chat.
These are the four areas where gpt-image-2 clearly outperforms the previous generation of image models. Each one works from a short prompt in the Genspark chat.
gpt-image-2 renders readable text directly inside the image — headlines, body copy, labels, and callouts — across Latin, CJK, Arabic, Hindi, and Bengali scripts. Crisp, not garbled. This is the single biggest jump over previous image models.
Upload up to 16 reference images in one request and ask for targeted edits: "change the background to sunset," "make the sofa leather," "keep the character but redraw in manga style." gpt-image-2 preserves what you didn't mention and rewrites only what you did — pixel-level, not regenerate-from-scratch.
Generate up to 4096×4096 resolution in a single pass, enough for print, product listings, and large-format social assets. Pick the tier that fits the job — 1K for quick drafts, 4K for final delivery — directly from the model selector in Genspark.
Non-Latin scripts finally render correctly. Ask for a Japanese event poster, a Korean menu card, an Arabic social graphic, or a Hindi infographic — and the text inside the image reads naturally, not as boxes or fake glyphs. A real unlock for teams shipping into non-English markets.
These are categories where gpt-image-2 produces ship-quality output on the first try — not just rough drafts. Use the example prompts above or describe your own version.
Concerts, festivals, launches, campus events. Give the AI the title, date, location, and visual mood; the model handles typography, layout, and a matching background illustration in one pass.
Bar charts, stat blocks, process diagrams — the numbers and labels inside the image actually say what you wrote. Works well for pitch decks, blog headers, and social share cards.
Give a name and a vibe and get a logo mark, a matching color palette, and typography samples laid out on one page. A fast way to start a brand identity for a new project or launch.
gpt-image-2 is a general-purpose model, but the jump in text rendering and multilingual support makes it clearly better than the previous generation for these roles in particular.
Draft ad creatives, launch posters, and landing-page hero images with real headlines, real product names, and real offer text baked into the visual — no separate typesetting step.
Use it as a fast concepting tool: generate 5 directions in one sitting, pick the one that works, then take it into Figma or Photoshop for final polish. The multi-image edit flow keeps art direction consistent across revisions.
Thumbnails, cover art, episode headers, explainer diagrams. Describe the channel's vibe once, reuse that description across every piece of content to keep the look consistent.
Lifestyle shots on model-less backgrounds, variant swaps ("same bag in tan leather"), seasonal listing headers with readable promo text. All from a product photo plus a short description.
gpt-image-2 nails long sentences, multi-line layouts, exact typography, and case-sensitive punctuation. Posters, newspapers, and billboards come out production-ready, no manual relettering needed.
Built on a much deeper world model, gpt-image-2 hallucinates dramatically less than older models. Anatomy diagrams, geographic maps, ingredient layouts, and physical structures come out internally consistent and labelable.
Up to 4096×4096 native resolution and aspect ratios up to 3:1, with output sharp enough for printed billboards, magazine spreads, and high-DPI digital ad placements straight out of the model.
Long, multi-paragraph prompts with exact layouts, named characters, specific outfits, and pixel-precise typography all land on the first try. Below are the verbatim prompts and the unedited outputs gpt-image-2 produced.
Generate a single character turnaround sheet for a high-school anime protagonist named Kai. Top row shows three full-body angles labeled FRONT, SIDE, 3/4 BACK in his navy school blazer, white shirt, red tie, grey trousers, and black leather shoes. Bottom row shows three head-and-shoulders portraits of the same character with the labels HAPPY, ANGRY, SURPRISED. Identical hair, face, and outfit across all six panels, neutral white reference-sheet background, soft even lighting.
Generate a clean DTC product detail page mockup for a tan full-grain Italian leather tote called Classic Tote by the brand North & Pine. Left half shows a single hero photo of the bag on a soft cream studio background. Right half shows the brand label "// NORTH & PINE", product name set in elegant serif, the price "$420", a short description ending with "Holds a 13-inch laptop.", three round color swatches labeled black/tan/olive, three size pills S/M/L with M selected, and a wide navy "Add to Cart" button. Crisp typography, airy modern e-commerce aesthetic.
Generate a four-panel black-and-white manga page about a young woman receiving a handwritten letter from someone she has not seen in years. Panel 1: she sits alone in a Tokyo cafe by a rainy window, reading the letter, a thought bubble in Japanese says 彼が帰ってきた. Panel 2: an exterior wide shot of the same cafe with neon-lit Tokyo skyline behind it. Panel 3: a quiet close-up of her looking out the window. Panel 4: a top-down macro of her hands holding the open letter, the visible handwritten kanji legible. Same character design across all four panels, soft cinematic shading.
Conversational edits land surgically: backgrounds swap, outfits change, seasons turn — all without the rest of the image drifting. Lighting, shadows, skin tones, and composition stay locked.
01Write a short prompt — subject, style, layout, and any exact text you want rendered inside the image. Genspark's chat accepts plain language in any of 19 supported UI languages.
02In the model selector, choose GPT Image 2 and pick a size (1K / 2K / 3K / 4K) plus quality (auto / low / medium / high). Start with 1K-medium for fast drafts; switch to 4K-high for final delivery.
03Genspark returns the image in a few seconds. Not quite right? Keep the conversation going — send an edit instruction like "move the headline higher" or attach a reference and the model rewrites just that part.
This page is focused on what gpt-image-2 does best. If your workflow shifts toward another job, these nearby Genspark tools are better starting points.
Yes — every Genspark account gets 100 free credits refreshed daily, and you can spend them on gpt-image-2. The fastest 1K tiers fit inside the free daily allowance (for example, 1K-low costs 5 credits per image). For heavy use or higher tiers like 4K-high, Plus and Pro plans give a much larger monthly credit balance.
Same thing. ChatGPT Images 2.0 is the product name users see inside ChatGPT; gpt-image-2 is the API model name. Genspark calls the API directly, so you're using exactly the same underlying model.
Yes. Attach up to 16 reference images in the chat and describe the change you want. gpt-image-2 handles pixel-level edits — background swaps, material changes, added or removed elements — while preserving the parts of the image you didn't ask to change.
Four size tiers (1K / 2K / 3K / 4K, up to 4096×4096) and four quality levels (auto / low / medium / high). The default is 1K-medium, which is a good balance of speed and clarity; bump to 4K-high for print, product listings, or large-format social assets.
Yes. Non-Latin script rendering is one of the flagship improvements in this release — accuracy is close to Latin-script levels. You can ask for a Japanese event poster, a Korean menu card, or an Arabic announcement graphic and the text inside the image reads naturally.
No. OpenAI blocks generations of copyrighted IP at the model level. Use original, generic descriptions — "a friendly yellow electric mouse-like creature," "a red-capped plumber hero in a cartoon kingdom" — and the model creates an original character in that spirit.