GPT-image-2 AI Image API
GPT Image 2 is OpenAI's image-generation model. OpenAI documents image generation and editing with flexible sizes; Flatkey exposes the image routes and request controls shown below.
Output
Preview
Request summary
- Endpoint
- POST /v1/images/generations
- Model ID
- GPT-image-2
- Aspect ratio
- 283:400
- Resolution
- 1024x1024
- Quality
- high
- Outputs
- 1
Preview only. Sign in to submit this request to Flatkey.
{
"model": "gpt-image-2",
"prompt": "Goal: Create a vertical ancient-Chinese style literature teaching PPT poster analyzing {argument name=\"work title\" default=\"登岳阳楼记\"}, with an ink-wash historical illustration, dense text-and-image layout, and Song/Yuan classroom handout aesthetics.\n\nCanvas: Portrait 3:4 poster, warm off-white rice paper background with subtle fibers, gray ink stains, light cloud textures, aged edges, and muted black, sepia, red seal, and pale blue-gray tones. High information density but elegant and readable.\n\nLayout: Top third contains a huge expressive black brush-calligraphy title across the page, with a small red seal and a vertical author label at the upper right. Under the title, place two centered subtitle lines in small serif Chinese type: “洞庭天下水,岳阳天下楼” and “以楼观湖,以景寄志,以文见心”. The left column is a structured knowledge-analysis panel; the center contains three large quoted key sentences; the right half is dominated by a dramatic Yueyang Tower illustration above cliffs and Dongting Lake. Bottom third contains comparison cards, a location map, two small literary reference cards, an author-ideal card, and a keyword strip.\n\nMain illustration: Paint Yueyang Tower as a multi-eaved traditional wooden pavilion on a high rocky cliff, facing a vast misty lake at sunset. Include layered mountains, drifting clouds, birds, tiny boats on the lake, water reflections, rugged rocks, pine-like vegetation, and mist rising from the cliff. At lower right, show one robed ancient Chinese scholar seen from behind in gray ink, standing on rocks and looking toward the tower. Add a vertical inscription beside the tower reading “洞庭天下水 / 岳阳天下楼” with a small red seal.\n\nLeft knowledge panel: Use a vertical heading in a gray ink blot reading “知识解析”. Include exactly 8 numbered analysis items, each with a circled number and short Chinese body text: 1 Author, 2 Text genre, 3 Creative background, 4 Place, 5 Famous sentence, 6 Structural features, 7 Emotional layers, 8 Cultural meaning. Add one small red boxed date label near item 3 reading “庆历六年”. Keep all text compact, like a teaching slide.\n\nCenter quote section: Add a narrow vertical label reading “核心引文”. Include exactly 3 large quoted excerpts, separated by thin decorative horizontal rules with small red dots: “先天下之忧而忧,后天下之乐而乐。”; “此则岳阳楼之大观也。”; “览物之情,得无异乎?”.\n\nBottom middle comparison card: Draw a bordered cream card titled “情景对照:景随情转,借由景生”. Inside it, create exactly 2 contrasting columns: left column “阴雨霏霏” describing gloomy rain, waves, and melancholy; right column “春和景明” describing bright spring, calm waves, and joy. Put a round center badge reading “对照”, with small ink cloud and sun doodles.\n\nBottom information row: Create exactly 4 boxed sections from left to right. Section 1 is a “位置示意” location card with a simplified map of Hunan and a red dot labeled “湖南·岳阳”. Section 2 is a Dongting Lake card titled “洞庭湖” with a small sailboat illustration and brief notes about vast lake water and mist. Section 3 is a reference card titled “巴陵胜状(节选)” with a small mountain-water sketch and brief excerpt text. Section 4 is a card titled “士大夫人格理想” explaining concern for the world, responsibility, and moral character.\n\nBottom keyword strip: Add a red label “关键词”, followed by exactly 6 keyword groups separated by slashes and small icons: “岳阳楼”, “洞庭湖”, “忧乐精神”, “家国情怀”, “北宋散文”, “千古名篇”. Add two small red square seal stamps at the bottom right.\n\nTypography and style: Combine bold wild brush calligraphy for the title, neat traditional Chinese serif type for educational notes, and thin line dividers. Use ink-wash realism mixed with PPT infographic layout. Keep all visible text in Chinese, crisp and legible. Avoid modern sans-serif UI styling, neon colors, cartoon effects, watermarks, or English text.",
"n": 1,
"size": "1024x1024",
"quality": "high",
"output_format": "png",
"background": "opaque",
"moderation": "auto"
}Performance
GPT Image 2 API performance and availability
Live Flatkey request telemetry appears here when enough image-generation traffic is available.
Activity
GPT Image 2 API usage and generation activity
This chart reflects live Flatkey generation requests and remains unreported until enough traffic is collected.
Pricing
GPT-image-2 Pricing
GPT-image-2 pricing here follows the current Flatkey catalog unit, not an assumed OpenAI direct tariff. Set image size, quality and output count before estimating cost. For edits, supply reference images and describe what must stay unchanged.
Add credits
Use the same Flatkey balance and API key across image, video, audio, and text models.
- Model Type
- Text to Image
- API
- /v1/images/generations
- Billing basis
- image
- Outputs
- 1–10
GPT Image 2 image generation and editing capabilities
Use the documented image workflows for new visuals, reference-led edits, and production-ready creative variants.
Text-to-image creation
Generate new product, editorial, and campaign visuals from a structured natural-language prompt.
Reference-based editing
Supply an image input to revise an existing visual while preserving important subject and composition details.
Flexible image composition
Create square, portrait, or landscape assets with flexible image sizes for different placements and channels.
High-fidelity visual input
Combine text and image context in one workflow for richer visual direction; audio and video inputs are not supported by this model.
Compare
GPT Image 2 and GPT Image 1: image API controls
GPT Image 1 values are not verified in this fact set, so only documented GPT Image 2 fields are shown.
| Capability | GPT Image 1 | GPT Image 2 |
|---|---|---|
| Endpoints | Unknown here | /v1/images/generations; /v1/images/edits |
| Sizes | Unknown here | 1024x1024, 1536x1024, 1024x1536, auto |
| Formats | Unknown here | PNG, JPEG, WebP |
| Quality/background/moderation | Unknown here | Documented above |
| Image quality ranking | Not asserted | Not asserted |
Choose the right request before you integrate
Review the supported workflows, live cost for the current setup, and the exact parameter contract used by Flatkey.
Calculated from the current Playground settings and the live catalog rate when a fixed unit price is available.
- Current setup
- 1024x1024 · high · 1×
- Live rate
- $0.0066 / image
- Estimated request
- $0.0066
The final charge follows the submitted request and your account group. Token-priced or tiered requests cannot be reduced to one fixed estimate.
Workflows and Model ID
Use only the workflows marked available. Flatkey keeps one public model ID while the request body selects the input workflow.
Text to Image
Generate a new image from a text prompt and output controls.
- Model ID
gpt-image-2- Endpoint
/v1/images/generations
Reference-guided Image
Use reference images for edits, variations, or identity and composition guidance.
- Model ID
gpt-image-2- Endpoint
/v1/images/generations
Parameter compatibility
These values come from the same model configuration used by the Playground and request preview.
nImages1–10
Default: 1sizeSize1024x1024 · 1536x1024 · 1024x1536 · auto
Default: 1024x1024qualityQualityauto · high · medium · low
Default: highoutput_formatOutput formatpng · jpeg · webp
Default: pngbackgroundBackgroundopaque · auto
Default: opaquemoderationModerationauto · low
Default: autoimageReference limit4 files
Endpoint: /v1/images/generationsFrom first test to production
Use the same request contract in the Playground and API, then handle validation, balance, task state, and output retrieval explicitly.
Request lifecycle
- 1
Validate the model, prompt, references, and output settings.
- 2
POST the image request with the documented fields.
- 3
Read the generated output or asynchronous task result returned by the route.
- 4
Store the generated file and request metadata in your own workflow.
Production checks
Reject unsupported sizes, durations, ratios, formats, or reference counts before submitting.
Handle invalid keys, insufficient balance, rate limits, and account-group pricing separately.
Surface the rejected prompt or asset clearly so the user can replace only the failing input.
Keep the task ID, use bounded retries, and never treat a timeout as a successful generation.
Prompt library
GPT Image 2 prompt examples for product and marketing visuals
Start with a concrete subject, composition, output size, and brand constraint; adjust the request fields separately.
Generated with Image 2
Scene: A 16:9 sci-fi game loadout screen in a blue-purple spaceship hangar. A female armored character stands centered with a glowing violet rifle; armor slots line the left, three weapon slots line the right, and the lower slot is highlighted. Keep the HUD hierarchy, pose, lighting, and equipment geometry fixed for an exact equipment-switch frame. No readable words, logos, invented stats, or watermark. Composition and rendering: Deliver one 16:9 game-interface keyframe. Separate the character, held equipment and HUD into clear depth layers; keep slot spacing and icon scale consistent, with the selected item visually dominant. Preserve the scene-specific game art style. Let material edges catch the existing light without letting interface glow obscure the silhouette. Keep all equipment fully inside the frame. Avoid: warped perspective, malformed anatomy, merged objects, inconsistent shadows, excessive sharpening and watermarks. Follow the scene-specific text and branding restrictions above.
Generated with Image 2
Scene: A rainy night soccer broadcast frame under bright stadium floodlights. A black-uniform player strikes the ball while two white-uniform defenders close in, with the goal and a blurred crowd behind. Keep the broadcast camera angle, blank blue score bars, spray, and motion blur consistent; leave overlays abstract and text-free. No real teams, athletes, logos, or watermark. Composition and rendering: Deliver one 16:9 broadcast still at the decisive instant. Use coherent perspective for the playing surface and equipment, readable separation between competitors, and a softer crowd behind the action. Keep the principal subject sharp, with directional blur limited to fast extremities and spray. Preserve the specified broadcast angle and reserve overlay areas clear of the action. Avoid: warped perspective, malformed anatomy, merged objects, inconsistent shadows, excessive sharpening and watermarks. Follow the scene-specific text and branding restrictions above.
Generated with Image 2
Scene: A closed matte-black square smartwatch with a black strap rests on a wet glossy black tabletop. Water droplets catch a cool blue rim light and a soft reflection sits beneath the watch. Use a low three-quarter product camera and preserve the case, strap, highlights, and empty dark background. No readable branding, extra products, hands, or watermark. Composition and rendering: Deliver one 16:9 commercial product still. Keep the complete product silhouette inside generous crop-safe margins. Resolve edges, seams and material transitions precisely; shape highlights to describe volume without clipping bright surfaces or crushing dark details. Align reflections with the object and light source. Retain the stated camera angle and existing negative space; add no decorative props. Avoid: warped perspective, malformed anatomy, merged objects, inconsistent shadows, excessive sharpening and watermarks. Follow the scene-specific text and branding restrictions above.
Generated with Image 2
Scene: On a rain-soaked observatory roof at sunrise, a lone figure in a long dark coat walks toward a large telescope beside an open dome. Wet stone reflects the warm doorway light; cloud-covered mountains sit beyond. Hold the screen direction and end on the telescope and figure in the same wide composition. No readable text, logos, or watermark. Composition and rendering: Deliver one 16:9 storyboard keyframe, not a collage or an action sequence. Separate foreground, character plane and background through the existing light and atmospheric depth. Keep the stated pose and eyelines readable, and retain environmental landmarks for continuity. Match the described photographic, illustrated or puppet medium; give fabric and surfaces texture appropriate to that medium. Avoid: warped perspective, malformed anatomy, merged objects, inconsistent shadows, excessive sharpening and watermarks. Follow the scene-specific text and branding restrictions above.
Generated with Image 2
Scene: In a bright home kitchen, a surprised cook in a blue shirt and cream apron reaches toward pancakes, a frying pan, flour, bowl, and whisk suspended midair. Freeze the comic cause-and-effect moment with believable weight, warm daylight, and a clear path for each object. No injury, logos, readable words, or watermark. Composition and rendering: Deliver one 16:9 physical-comedy still at the described instant. Make the cause of the gag readable through body balance, grip and object spacing. Separate the reaction from the airborne props; retain believable gravity and contact points. Keep the face and important props sharp, with only restrained directional blur on fast edges. Preserve the stated lighting and room or stage layout. Avoid: warped perspective, malformed anatomy, merged objects, inconsistent shadows, excessive sharpening and watermarks. Follow the scene-specific text and branding restrictions above.
Generated with Image 2
Scene: A rainy period harbor platform shelters people in era-appropriate coats and umbrellas as a vintage green tram arrives on wet tracks. Wooden waterfront buildings and misty mountains sit behind the reflections. Preserve the historical clothing, tram shape, rain direction, and stable wide composition; no readable signage, logos, or watermark. Composition and restoration: Deliver one 16:9 archival-style still. Preserve the original framing, period-specific construction and restrained tonal range; retain monochrome, sepia or faded color as described. Recover modest detail in faces, clothing and architecture without synthetic sharpening. Keep fine grain and authentic aging consistent across the frame; repair damage without replacing historical features. Avoid: warped perspective, malformed anatomy, merged objects, inconsistent shadows, excessive sharpening and watermarks. Follow the scene-specific text and branding restrictions above.
Why use Flatkey for GPT Image 2?
A repeatable GPT Image 2 workflow for product images
Keep image controls and image-input token dimensions together so a prompt test can become a reproducible API request.
All documented controls in one place
Set n, size, quality, output format, background, and moderation before you hand the request to the console.
Image input stays explicit
The catalog exposes token and image-input dimensions; this is not a separate fee for output pixel size, and the final amount depends on request and usage fields.
Marketing-ready starting points
Use product, ad, and storyboard examples as editable starting prompts rather than generic image filler.
No unsupported promises
The page does not promise transparent output, free generation, or a fixed per-image price when those facts are not verified.
API
GPT-image-2 API
Four ways in, all on the same key and the same model catalog. Pick one to see a runnable example.
curl https://router.flatkey.ai/v1/images/generations \ -H "Content-Type: application/json" \ -H "Authorization: Bearer sk-***" \ -d '{"model":"gpt-image-2","prompt":"Create a high-quality product image with GPT-image-2: clean composition, precise lighting, strong subject focus, and realistic detail.","n":1,"size":"1024x1024","quality":"high","output_format":"png","background":"opaque","moderation":"auto"}'
FAQ
GPT Image 2 API
pricing and prompt questions
Answers about GPT Image 2 API access, image-generation fields, token and image-input pricing, formats, and background behavior.





