Chrome ExtensionGPT Image 2 Prompt Generator
Generate optimized prompts for OpenAI's GPT Image 2 — the autoregressive image model with 99% English text accuracy, multilingual rendering, native 2K output, and O-series reasoning. Built around the official OpenAI cookbook's five-part structure (Scene → Subject → Details → Use Case → Constraints) with anti-slop rules and edit-mode discipline baked in.
Be specific: describe who/what is in the image with details
Quick Palettes
Generated Prompt
Fill in the form and click "Generate" to create an optimized GPT Image 2 prompt.
Tip: Be as specific as possible with your subject description. Instead of "a dog," try "a golden retriever puppy with a red bandana."
GPT Image 2 Tips
- • Structure: Scene → Subject → Important Details → Use Case → Constraints
- • Anti-slop: replace "stunning/masterpiece/8K" with concrete facts ("overcast daylight," "50mm feel," "brushed aluminum")
- • Text rendering is GPT Image 2's superpower — quote literal text, specify font/size/color/placement, spell tricky words letter-by-letter
- • For edits, always say "Change only X, keep everything else the same" and repeat the preserve list each iteration
- • Multilingual text works in CJK, Hindi, Bengali, Arabic — preserve typography style across languages
- • Use Medium/High quality for dense text, multi-font layouts, or identity-sensitive edits
How to Use the Prompt Generator
Pick Mode & Describe Your Vision
Choose Generate, Edit, or Combine. Pick a use case category (infographic, slide, manga panel, product photo, UI mockup, etc.), set quality and reasoning mode, then describe your scene and subject. For edits, fill in the “Preserve” field so identity, layout, and brand elements stay locked.
Generate Your Prompt
Click Generate. The tool assembles your inputs into the OpenAI cookbook's five-part structure, swaps vague praise for concrete visual facts, formats text-in-image directives correctly, and adds a preserve list when you're editing — so the output drops straight into ChatGPT or the API.
Copy & Create
Paste into ChatGPT, the OpenAI API (model: “gpt-image-2”), or Codex. For iterative edits, use the prompt as a base and follow up with single small changes — repeat the preserve list each iteration to prevent drift.
Frequently Asked Questions
What is GPT Image 2?
GPT Image 2 (also called ChatGPT Images 2.0) is OpenAI's next-generation image model, released April 21, 2026. It uses autoregressive token-by-token generation (the same approach as a language model) and ships with major upgrades: 99% English text rendering accuracy, 90%+ accuracy in Chinese, Japanese, Korean, Hindi, Bengali, and Arabic, native 2K resolution, O-series reasoning in Thinking mode, and support for up to 16 reference images per edit.
How does this prompt generator work?
You fill in structured inputs — scene, subject, style, composition, lighting, intended use, generation mode, and constraints. Our AI assembles them into the OpenAI cookbook's recommended five-part structure (Scene → Subject → Important Details → Use Case → Constraints) and applies anti-slop rules, typography directives, and edit-mode discipline so the prompt is production-ready.
What changed from GPT Image 1.5 to GPT Image 2?
GPT Image 2 brings: dramatically better text rendering (including small text, dense info panels, and multi-font layouts), multilingual scripts that previously failed, native 2K output (with experimental 4K), Thinking mode for layout reasoning and output verification, character/object continuity across batched generations, up to 16 reference images per edit, and the input_fidelity parameter is no longer needed because output is already high fidelity by default.
What are Generate, Edit, and Combine modes?
GPT Image 2 has three operating modes. Generate creates an image from text alone. Edit modifies a single input image — write your prompt as "Change only X, keep everything else the same," then list what to preserve. Combine references multiple images by index ("Image 1: base scene. Image 2: jacket reference") and describes how they should interact. Pick the mode that matches your workflow.
What is Thinking (Reasoning) Mode?
Thinking mode unlocks O-series reasoning capabilities: layout planning for slides and infographics, multi-image batching with character continuity, web search lookups for accurate references, and output verification before final render. Use it for complex briefs that benefit from planning — multi-page slide decks, labeled maps, scientific diagrams, or character-consistent series work. Instant mode is fine for single-shot generation.
How accurate is text rendering in GPT Image 2?
GPT Image 2 hits 99% accuracy on English text and 90%+ on Chinese, Japanese, Korean, Hindi, Bengali, and Arabic. To get the best results: wrap literal text in quotes or ALL CAPS, specify font style and color, state placement explicitly, and spell tricky brand names letter-by-letter. For dense or small text, use Medium or High quality.
When should I pick Low vs Medium vs High quality?
Low is best for high-volume generation, experimentation, and latency-sensitive workflows — fidelity is still good. Medium is the balanced production default for social posts and editorial work. High is for dense text, fine typography, identity-sensitive edits, close-up portraits, and print-ready output.
Why is "anti-slop" language important?
GPT Image 2 ignores vague praise like "stunning," "masterpiece," "ultra-detailed," or "8K." It responds far more reliably to concrete visual facts — "overcast daylight," "brushed aluminum," "50mm feel," "soft bounce light," "matte ceramic." Our generator strips out filler and substitutes specific camera, material, and lighting language.
Is this tool free to use?
Yes. You get 3 free prompt generations per day with no signup required. For unlimited access, sign up for a Promptslove membership which includes all AI tools and 20,000+ premium prompts.
Where can I use the generated prompts?
The prompts are tuned for GPT Image 2 via ChatGPT, the OpenAI API (model: "gpt-image-2"), and Codex. They also produce strong results on Midjourney, FLUX.2, Nano Banana 2, Seedream 5, and Stable Diffusion thanks to the structured, concrete language.
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