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gpt-image-2

Educational Vocabulary Poster

Structured educational vocabulary poster prompt for GPT Image 2.

Structured educational vocabulary poster prompt for GPT Image 2.
Structured educational vocabulary poster prompt for GPT Image 2.
Prompt

{ "type": "educational vocabulary poster", "style": "{argument name=\"art style\" default=\"isometric voxel 3D pixel art, Minecraft aesthetic, vibrant colors\"}", "scene": "Blocky room with a large wooden table covered in a blue and white checkered tablecloth. A window on the left shows a blocky sunrise landscape. A wooden cabinet, bookshelf, and wall clock are in the background.", "characters": [ "{argument name=\"main character\" default=\"blocky girl with brown pigtails in a pink shirt\"} sitting at the center of the table holding a fork.", "A smaller version of the girl at the bottom right, happily eating a slice of watermelon." ], "layout": { "title_sign": "Wooden block board at top left reading '{argument name=\"poster title\" default=\"My Colourful Breakfast\"}'", "speech_bubble": "Pointing to the center girl, reading '{argument name=\"speech text\" default=\"Yummy!\"}'", "vocabulary_cards_count": 15, "vocabulary_cards": [ { "item": "wall clock", "label": "time /taɪm/ 时间" }, { "item": "center girl", "label": "breakfast /brekfəst/ 早餐, 早饭" }, { "item": "sliced bread", "label": "bread /bred/ 面包" }, { "item": "fried egg", "label": "egg /eg/ (作食物用的) 蛋, 鸡蛋" }, { "item": "milk carton and glass", "label": "milk /mɪlk/ (牛式羊等的) 奶" }, { "item": "bowl of noodles", "label": "noodle /'nu:dl/ (常用复数) 面条" }, { "item": "glass of orange juice", "label": "juice /dʒu:s/ 果汁" }, { "item": "bowl of white rice", "label": "rice /raɪs/ 大米" }, { "item": "plate of meat cubes", "label": "meat /mi:t/ 肉" }, { "item": "plate of broccoli and carrots", "label": "vegetable /vedʒtəbl/ 蔬菜" }, { "item": "large green leaf", "label": "healthy /helθi/ 健康的" }, { "item": "empty plate", "label": "plate /pleɪt/ 盘子" }, { "item": "plate of mixed fruit", "label": "fruit /fru:t/ 水果" }, { "item": "bowl of candies", "label": "candy /kændi/ 糖果" }, { "item": "girl eating watermelon", "label": "yummy /jʌmi/ 很好吃的" } ] } }

Prompt structure
  • Modelgpt-image-2
  • Use casecampaign-poster
  • Style3d-render, editorial, isometric
  • Aspect ratioFlexible
Best used for
  • Use casecampaign-poster
  • Style3d-render, editorial, isometric
  • Recommended specs1:1, 4:5, 16:9, or 9:16
  • ModelGPT Image 2
How to customize

Use this Educational Vocabulary Poster prompt as a base. Replace the subject, product details, environment, lighting, brand colors, and output ratio while keeping the campaign-poster intent and 3d-render, editorial, isometric direction stable.

Editable variables
  • SubjectReplace the product, person, scene, interface, or object being generated.
  • Use caseKeep or rewrite the destination as campaign poster, ad creative, cover image, poster, or ecommerce hero.
  • FrameChoose 1:1, 4:5, 16:9, or 9:16 based on the final placement.
  • Brand cuesAdd colors, materials, props, text-safe space, and the platform where the image will be used.
Recommended specs

Choose the frame for the destination first, then use 1K, 2K, or 4K based on output quality needs. Product images and posters usually benefit from higher resolution.

Pre-generation checklist
  • CheckSubject, lighting, composition, and frame are specific enough to review.
  • CheckText-safe space is included when the image will carry a headline or ad copy.
  • CheckResolution, credit cost, and final destination are checked before generation.
Why this prompt works

Educational Vocabulary Poster works because it starts from the image job, then controls subject, composition, lighting, style, and frame. It is best for campaign poster while keeping the 3d-render, editorial, isometric direction stable.

Common questions
  • Can I use it directly?Yes. Replace the subject, brand cues, and frame, then generate in Image2Studio.
  • Which ratio should I use?Choose 1:1, 4:5, 16:9, or 9:16 based on the destination.