MODEL PROMPTS

gpt-image-2 Prompts — 297 curated examples

Examples for using gpt-image-2 through RunAPI from agent tools or API calls. Copy a prompt, then use it in Claude Code, Codex, Cursor, Windsurf, or your backend.

MODELS

gpt-image-2

Modality
Image
Provider
OpenAI
Endpoint
Text To Image
View model details and pricing →
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. Restart Claude Code
3. Paste this prompt: Generate an image: "{ "master_prompt": { "global_settings": { "resolution": "8K ultra-high-definition", "aspect_ratio": "3:4 vertical", "style": "hyper-realistic AI-edited commercial product photography", "sharpness": "extreme clarity, micro-detail visibility", "lighting_quality": "cinematic studio lighting with controlled highlights and shadows", "motion_freeze": "high-speed capture, frozen splashes and particles", "noise": "none", "artifacts": "none" }, "module_1_image_1_style": { "subject": { "type": "plastic protein drink bottle", "color": "deep matte blue", "surface_details": "condensation droplets across entire bottle", "label_text_visible": [ "milk & yogurt", "mock up", "protein", "SEPARATED SHADOWS" ] }, "pose_and_orientation": { "position": "slightly tilted to the right", "angle": "three-quarter view", "motion_feel": "dynamic, leaning into splash" }, "liquid_and_motion": { "liquid_color": "white and light beige milk mixture", "texture": "smooth, creamy, fluid", "motion": "swirling splash rising around bottle base and sides" }, "floating_elements": { "blueberries": "whole and halved blueberries at different depths", "mint_leaves": "small green leaves with visible veins", "droplets": "milk droplets and spheres suspended mid-air" }, "background": { "color_gradient": "dark blue to warm amber", "bokeh": "soft circular light particles scattered throughout" }, "surface_and_reflection": { "base": "matte ground with light liquid pooling", "shadow_style": "soft separated shadow under bottle" } }, "module_2_image_2_style": { "subject": { "type": "metal coffee can", "color": "warm gold", "surface_details": "heavy condensation with visible droplets", "branding_text_visible": [ "NESCAFÉ", "Latte", "NEW LOOK", "ICED COFFEE WITH MILK", "SUGAR AND SWEETENER OPTIONAL" ] }, "pose_and_orientation": { "position": "upright, centered", "angle": "front-facing", "presence": "hero product stance" }, "liquid_and_motion": { "liquid_color": "coffee and milk blend", "motion": "splash erupting from base", "droplet_behavior": "fine droplets scattered outward" }, "floating_elements": { "coffee_beans": "whole roasted beans floating around can", "steam": "thick swirling steam rising upward", "embers": "tiny glowing particles in background" }, "background": { "color_palette": "deep brown, amber, gold", "atmosphere": "warm, smoky, intense" }, "surface_and_reflection": { "base": "wet surface with liquid splash crown", "reflection_quality": "subtle reflective highlights" } }"
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate an image: "{ "master_prompt": { "global_settings": { "resolution": "8K ultra-high-definition", "aspect_ratio": "3:4 vertical", "style": "hyper-realistic AI-edited commercial product photography", "sharpness": "extreme clarity, micro-detail visibility", "lighting_quality": "cinematic studio lighting with controlled highlights and shadows", "motion_freeze": "high-speed capture, frozen splashes and particles", "noise": "none", "artifacts": "none" }, "module_1_image_1_style": { "subject": { "type": "plastic protein drink bottle", "color": "deep matte blue", "surface_details": "condensation droplets across entire bottle", "label_text_visible": [ "milk & yogurt", "mock up", "protein", "SEPARATED SHADOWS" ] }, "pose_and_orientation": { "position": "slightly tilted to the right", "angle": "three-quarter view", "motion_feel": "dynamic, leaning into splash" }, "liquid_and_motion": { "liquid_color": "white and light beige milk mixture", "texture": "smooth, creamy, fluid", "motion": "swirling splash rising around bottle base and sides" }, "floating_elements": { "blueberries": "whole and halved blueberries at different depths", "mint_leaves": "small green leaves with visible veins", "droplets": "milk droplets and spheres suspended mid-air" }, "background": { "color_gradient": "dark blue to warm amber", "bokeh": "soft circular light particles scattered throughout" }, "surface_and_reflection": { "base": "matte ground with light liquid pooling", "shadow_style": "soft separated shadow under bottle" } }, "module_2_image_2_style": { "subject": { "type": "metal coffee can", "color": "warm gold", "surface_details": "heavy condensation with visible droplets", "branding_text_visible": [ "NESCAFÉ", "Latte", "NEW LOOK", "ICED COFFEE WITH MILK", "SUGAR AND SWEETENER OPTIONAL" ] }, "pose_and_orientation": { "position": "upright, centered", "angle": "front-facing", "presence": "hero product stance" }, "liquid_and_motion": { "liquid_color": "coffee and milk blend", "motion": "splash erupting from base", "droplet_behavior": "fine droplets scattered outward" }, "floating_elements": { "coffee_beans": "whole roasted beans floating around can", "steam": "thick swirling steam rising upward", "embers": "tiny glowing particles in background" }, "background": { "color_palette": "deep brown, amber, gold", "atmosphere": "warm, smoky, intense" }, "surface_and_reflection": { "base": "wet surface with liquid splash crown", "reflection_quality": "subtle reflective highlights" } }"
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate an image: "{ "master_prompt": { "global_settings": { "resolution": "8K ultra-high-definition", "aspect_ratio": "3:4 vertical", "style": "hyper-realistic AI-edited commercial product photography", "sharpness": "extreme clarity, micro-detail visibility", "lighting_quality": "cinematic studio lighting with controlled highlights and shadows", "motion_freeze": "high-speed capture, frozen splashes and particles", "noise": "none", "artifacts": "none" }, "module_1_image_1_style": { "subject": { "type": "plastic protein drink bottle", "color": "deep matte blue", "surface_details": "condensation droplets across entire bottle", "label_text_visible": [ "milk & yogurt", "mock up", "protein", "SEPARATED SHADOWS" ] }, "pose_and_orientation": { "position": "slightly tilted to the right", "angle": "three-quarter view", "motion_feel": "dynamic, leaning into splash" }, "liquid_and_motion": { "liquid_color": "white and light beige milk mixture", "texture": "smooth, creamy, fluid", "motion": "swirling splash rising around bottle base and sides" }, "floating_elements": { "blueberries": "whole and halved blueberries at different depths", "mint_leaves": "small green leaves with visible veins", "droplets": "milk droplets and spheres suspended mid-air" }, "background": { "color_gradient": "dark blue to warm amber", "bokeh": "soft circular light particles scattered throughout" }, "surface_and_reflection": { "base": "matte ground with light liquid pooling", "shadow_style": "soft separated shadow under bottle" } }, "module_2_image_2_style": { "subject": { "type": "metal coffee can", "color": "warm gold", "surface_details": "heavy condensation with visible droplets", "branding_text_visible": [ "NESCAFÉ", "Latte", "NEW LOOK", "ICED COFFEE WITH MILK", "SUGAR AND SWEETENER OPTIONAL" ] }, "pose_and_orientation": { "position": "upright, centered", "angle": "front-facing", "presence": "hero product stance" }, "liquid_and_motion": { "liquid_color": "coffee and milk blend", "motion": "splash erupting from base", "droplet_behavior": "fine droplets scattered outward" }, "floating_elements": { "coffee_beans": "whole roasted beans floating around can", "steam": "thick swirling steam rising upward", "embers": "tiny glowing particles in background" }, "background": { "color_palette": "deep brown, amber, gold", "atmosphere": "warm, smoky, intense" }, "surface_and_reflection": { "base": "wet surface with liquid splash crown", "reflection_quality": "subtle reflective highlights" } }"
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate an image: "{ "master_prompt": { "global_settings": { "resolution": "8K ultra-high-definition", "aspect_ratio": "3:4 vertical", "style": "hyper-realistic AI-edited commercial product photography", "sharpness": "extreme clarity, micro-detail visibility", "lighting_quality": "cinematic studio lighting with controlled highlights and shadows", "motion_freeze": "high-speed capture, frozen splashes and particles", "noise": "none", "artifacts": "none" }, "module_1_image_1_style": { "subject": { "type": "plastic protein drink bottle", "color": "deep matte blue", "surface_details": "condensation droplets across entire bottle", "label_text_visible": [ "milk & yogurt", "mock up", "protein", "SEPARATED SHADOWS" ] }, "pose_and_orientation": { "position": "slightly tilted to the right", "angle": "three-quarter view", "motion_feel": "dynamic, leaning into splash" }, "liquid_and_motion": { "liquid_color": "white and light beige milk mixture", "texture": "smooth, creamy, fluid", "motion": "swirling splash rising around bottle base and sides" }, "floating_elements": { "blueberries": "whole and halved blueberries at different depths", "mint_leaves": "small green leaves with visible veins", "droplets": "milk droplets and spheres suspended mid-air" }, "background": { "color_gradient": "dark blue to warm amber", "bokeh": "soft circular light particles scattered throughout" }, "surface_and_reflection": { "base": "matte ground with light liquid pooling", "shadow_style": "soft separated shadow under bottle" } }, "module_2_image_2_style": { "subject": { "type": "metal coffee can", "color": "warm gold", "surface_details": "heavy condensation with visible droplets", "branding_text_visible": [ "NESCAFÉ", "Latte", "NEW LOOK", "ICED COFFEE WITH MILK", "SUGAR AND SWEETENER OPTIONAL" ] }, "pose_and_orientation": { "position": "upright, centered", "angle": "front-facing", "presence": "hero product stance" }, "liquid_and_motion": { "liquid_color": "coffee and milk blend", "motion": "splash erupting from base", "droplet_behavior": "fine droplets scattered outward" }, "floating_elements": { "coffee_beans": "whole roasted beans floating around can", "steam": "thick swirling steam rising upward", "embers": "tiny glowing particles in background" }, "background": { "color_palette": "deep brown, amber, gold", "atmosphere": "warm, smoky, intense" }, "surface_and_reflection": { "base": "wet surface with liquid splash crown", "reflection_quality": "subtle reflective highlights" } }"
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "gpt-image-2",
  "prompt": "{ \"master_prompt\": { \"global_settings\": { \"resolution\": \"8K ultra-high-definition\", \"aspect_ratio\": \"3:4 vertical\", \"style\": \"hyper-realistic AI-edited commercial product photography\", \"sharpness\": \"extreme clarity, micro-detail visibility\", \"lighting_quality\": \"cinematic studio lighting with controlled highlights and shadows\", \"motion_freeze\": \"high-speed capture, frozen splashes and particles\", \"noise\": \"none\", \"artifacts\": \"none\" }, \"module_1_image_1_style\": { \"subject\": { \"type\": \"plastic protein drink bottle\", \"color\": \"deep matte blue\", \"surface_details\": \"condensation droplets across entire bottle\", \"label_text_visible\": [ \"milk & yogurt\", \"mock up\", \"protein\", \"SEPARATED SHADOWS\" ] }, \"pose_and_orientation\": { \"position\": \"slightly tilted to the right\", \"angle\": \"three-quarter view\", \"motion_feel\": \"dynamic, leaning into splash\" }, \"liquid_and_motion\": { \"liquid_color\": \"white and light beige milk mixture\", \"texture\": \"smooth, creamy, fluid\", \"motion\": \"swirling splash rising around bottle base and sides\" }, \"floating_elements\": { \"blueberries\": \"whole and halved blueberries at different depths\", \"mint_leaves\": \"small green leaves with visible veins\", \"droplets\": \"milk droplets and spheres suspended mid-air\" }, \"background\": { \"color_gradient\": \"dark blue to warm amber\", \"bokeh\": \"soft circular light particles scattered throughout\" }, \"surface_and_reflection\": { \"base\": \"matte ground with light liquid pooling\", \"shadow_style\": \"soft separated shadow under bottle\" } }, \"module_2_image_2_style\": { \"subject\": { \"type\": \"metal coffee can\", \"color\": \"warm gold\", \"surface_details\": \"heavy condensation with visible droplets\", \"branding_text_visible\": [ \"NESCAFÉ\", \"Latte\", \"NEW LOOK\", \"ICED COFFEE WITH MILK\", \"SUGAR AND SWEETENER OPTIONAL\" ] }, \"pose_and_orientation\": { \"position\": \"upright, centered\", \"angle\": \"front-facing\", \"presence\": \"hero product stance\" }, \"liquid_and_motion\": { \"liquid_color\": \"coffee and milk blend\", \"motion\": \"splash erupting from base\", \"droplet_behavior\": \"fine droplets scattered outward\" }, \"floating_elements\": { \"coffee_beans\": \"whole roasted beans floating around can\", \"steam\": \"thick swirling steam rising upward\", \"embers\": \"tiny glowing particles in background\" }, \"background\": { \"color_palette\": \"deep brown, amber, gold\", \"atmosphere\": \"warm, smoky, intense\" }, \"surface_and_reflection\": { \"base\": \"wet surface with liquid splash crown\", \"reflection_quality\": \"subtle reflective highlights\" } }"
}
JSON
import { GptImage2Client } from "@runapi.ai/gpt-image-2";

const client = new GptImage2Client({
  apiKey: process.env.RUNAPI_API_KEY,
});

const result = await client.textToImage.run({
  "model": "gpt-image-2",
  "prompt": "{ \"master_prompt\": { \"global_settings\": { \"resolution\": \"8K ultra-high-definition\", \"aspect_ratio\": \"3:4 vertical\", \"style\": \"hyper-realistic AI-edited commercial product photography\", \"sharpness\": \"extreme clarity, micro-detail visibility\", \"lighting_quality\": \"cinematic studio lighting with controlled highlights and shadows\", \"motion_freeze\": \"high-speed capture, frozen splashes and particles\", \"noise\": \"none\", \"artifacts\": \"none\" }, \"module_1_image_1_style\": { \"subject\": { \"type\": \"plastic protein drink bottle\", \"color\": \"deep matte blue\", \"surface_details\": \"condensation droplets across entire bottle\", \"label_text_visible\": [ \"milk & yogurt\", \"mock up\", \"protein\", \"SEPARATED SHADOWS\" ] }, \"pose_and_orientation\": { \"position\": \"slightly tilted to the right\", \"angle\": \"three-quarter view\", \"motion_feel\": \"dynamic, leaning into splash\" }, \"liquid_and_motion\": { \"liquid_color\": \"white and light beige milk mixture\", \"texture\": \"smooth, creamy, fluid\", \"motion\": \"swirling splash rising around bottle base and sides\" }, \"floating_elements\": { \"blueberries\": \"whole and halved blueberries at different depths\", \"mint_leaves\": \"small green leaves with visible veins\", \"droplets\": \"milk droplets and spheres suspended mid-air\" }, \"background\": { \"color_gradient\": \"dark blue to warm amber\", \"bokeh\": \"soft circular light particles scattered throughout\" }, \"surface_and_reflection\": { \"base\": \"matte ground with light liquid pooling\", \"shadow_style\": \"soft separated shadow under bottle\" } }, \"module_2_image_2_style\": { \"subject\": { \"type\": \"metal coffee can\", \"color\": \"warm gold\", \"surface_details\": \"heavy condensation with visible droplets\", \"branding_text_visible\": [ \"NESCAFÉ\", \"Latte\", \"NEW LOOK\", \"ICED COFFEE WITH MILK\", \"SUGAR AND SWEETENER OPTIONAL\" ] }, \"pose_and_orientation\": { \"position\": \"upright, centered\", \"angle\": \"front-facing\", \"presence\": \"hero product stance\" }, \"liquid_and_motion\": { \"liquid_color\": \"coffee and milk blend\", \"motion\": \"splash erupting from base\", \"droplet_behavior\": \"fine droplets scattered outward\" }, \"floating_elements\": { \"coffee_beans\": \"whole roasted beans floating around can\", \"steam\": \"thick swirling steam rising upward\", \"embers\": \"tiny glowing particles in background\" }, \"background\": { \"color_palette\": \"deep brown, amber, gold\", \"atmosphere\": \"warm, smoky, intense\" }, \"surface_and_reflection\": { \"base\": \"wet surface with liquid splash crown\", \"reflection_quality\": \"subtle reflective highlights\" } }"
});
console.log(result.id);
require "runapi/gpt_image_2"

client = RunApi::GptImage2::Client.new
result = client.text_to_image.run(
  model: "gpt-image-2",
  prompt: "{ \"master_prompt\": { \"global_settings\": { \"resolution\": \"8K ultra-high-definition\", \"aspect_ratio\": \"3:4 vertical\", \"style\": \"hyper-realistic AI-edited commercial product photography\", \"sharpness\": \"extreme clarity, micro-detail visibility\", \"lighting_quality\": \"cinematic studio lighting with controlled highlights and shadows\", \"motion_freeze\": \"high-speed capture, frozen splashes and particles\", \"noise\": \"none\", \"artifacts\": \"none\" }, \"module_1_image_1_style\": { \"subject\": { \"type\": \"plastic protein drink bottle\", \"color\": \"deep matte blue\", \"surface_details\": \"condensation droplets across entire bottle\", \"label_text_visible\": [ \"milk & yogurt\", \"mock up\", \"protein\", \"SEPARATED SHADOWS\" ] }, \"pose_and_orientation\": { \"position\": \"slightly tilted to the right\", \"angle\": \"three-quarter view\", \"motion_feel\": \"dynamic, leaning into splash\" }, \"liquid_and_motion\": { \"liquid_color\": \"white and light beige milk mixture\", \"texture\": \"smooth, creamy, fluid\", \"motion\": \"swirling splash rising around bottle base and sides\" }, \"floating_elements\": { \"blueberries\": \"whole and halved blueberries at different depths\", \"mint_leaves\": \"small green leaves with visible veins\", \"droplets\": \"milk droplets and spheres suspended mid-air\" }, \"background\": { \"color_gradient\": \"dark blue to warm amber\", \"bokeh\": \"soft circular light particles scattered throughout\" }, \"surface_and_reflection\": { \"base\": \"matte ground with light liquid pooling\", \"shadow_style\": \"soft separated shadow under bottle\" } }, \"module_2_image_2_style\": { \"subject\": { \"type\": \"metal coffee can\", \"color\": \"warm gold\", \"surface_details\": \"heavy condensation with visible droplets\", \"branding_text_visible\": [ \"NESCAFÉ\", \"Latte\", \"NEW LOOK\", \"ICED COFFEE WITH MILK\", \"SUGAR AND SWEETENER OPTIONAL\" ] }, \"pose_and_orientation\": { \"position\": \"upright, centered\", \"angle\": \"front-facing\", \"presence\": \"hero product stance\" }, \"liquid_and_motion\": { \"liquid_color\": \"coffee and milk blend\", \"motion\": \"splash erupting from base\", \"droplet_behavior\": \"fine droplets scattered outward\" }, \"floating_elements\": { \"coffee_beans\": \"whole roasted beans floating around can\", \"steam\": \"thick swirling steam rising upward\", \"embers\": \"tiny glowing particles in background\" }, \"background\": { \"color_palette\": \"deep brown, amber, gold\", \"atmosphere\": \"warm, smoky, intense\" }, \"surface_and_reflection\": { \"base\": \"wet surface with liquid splash crown\", \"reflection_quality\": \"subtle reflective highlights\" } }"
)
puts result.id
package main

import (
  "context"
  "fmt"
  "log"
  "net/http"
  "os"
  "strings"
)

func main() {
  body := strings.NewReader("{\"model\":\"gpt-image-2\",\"prompt\":\"{ \\\"master_prompt\\\": { \\\"global_settings\\\": { \\\"resolution\\\": \\\"8K ultra-high-definition\\\", \\\"aspect_ratio\\\": \\\"3:4 vertical\\\", \\\"style\\\": \\\"hyper-realistic AI-edited commercial product photography\\\", \\\"sharpness\\\": \\\"extreme clarity, micro-detail visibility\\\", \\\"lighting_quality\\\": \\\"cinematic studio lighting with controlled highlights and shadows\\\", \\\"motion_freeze\\\": \\\"high-speed capture, frozen splashes and particles\\\", \\\"noise\\\": \\\"none\\\", \\\"artifacts\\\": \\\"none\\\" }, \\\"module_1_image_1_style\\\": { \\\"subject\\\": { \\\"type\\\": \\\"plastic protein drink bottle\\\", \\\"color\\\": \\\"deep matte blue\\\", \\\"surface_details\\\": \\\"condensation droplets across entire bottle\\\", \\\"label_text_visible\\\": [ \\\"milk & yogurt\\\", \\\"mock up\\\", \\\"protein\\\", \\\"SEPARATED SHADOWS\\\" ] }, \\\"pose_and_orientation\\\": { \\\"position\\\": \\\"slightly tilted to the right\\\", \\\"angle\\\": \\\"three-quarter view\\\", \\\"motion_feel\\\": \\\"dynamic, leaning into splash\\\" }, \\\"liquid_and_motion\\\": { \\\"liquid_color\\\": \\\"white and light beige milk mixture\\\", \\\"texture\\\": \\\"smooth, creamy, fluid\\\", \\\"motion\\\": \\\"swirling splash rising around bottle base and sides\\\" }, \\\"floating_elements\\\": { \\\"blueberries\\\": \\\"whole and halved blueberries at different depths\\\", \\\"mint_leaves\\\": \\\"small green leaves with visible veins\\\", \\\"droplets\\\": \\\"milk droplets and spheres suspended mid-air\\\" }, \\\"background\\\": { \\\"color_gradient\\\": \\\"dark blue to warm amber\\\", \\\"bokeh\\\": \\\"soft circular light particles scattered throughout\\\" }, \\\"surface_and_reflection\\\": { \\\"base\\\": \\\"matte ground with light liquid pooling\\\", \\\"shadow_style\\\": \\\"soft separated shadow under bottle\\\" } }, \\\"module_2_image_2_style\\\": { \\\"subject\\\": { \\\"type\\\": \\\"metal coffee can\\\", \\\"color\\\": \\\"warm gold\\\", \\\"surface_details\\\": \\\"heavy condensation with visible droplets\\\", \\\"branding_text_visible\\\": [ \\\"NESCAFÉ\\\", \\\"Latte\\\", \\\"NEW LOOK\\\", \\\"ICED COFFEE WITH MILK\\\", \\\"SUGAR AND SWEETENER OPTIONAL\\\" ] }, \\\"pose_and_orientation\\\": { \\\"position\\\": \\\"upright, centered\\\", \\\"angle\\\": \\\"front-facing\\\", \\\"presence\\\": \\\"hero product stance\\\" }, \\\"liquid_and_motion\\\": { \\\"liquid_color\\\": \\\"coffee and milk blend\\\", \\\"motion\\\": \\\"splash erupting from base\\\", \\\"droplet_behavior\\\": \\\"fine droplets scattered outward\\\" }, \\\"floating_elements\\\": { \\\"coffee_beans\\\": \\\"whole roasted beans floating around can\\\", \\\"steam\\\": \\\"thick swirling steam rising upward\\\", \\\"embers\\\": \\\"tiny glowing particles in background\\\" }, \\\"background\\\": { \\\"color_palette\\\": \\\"deep brown, amber, gold\\\", \\\"atmosphere\\\": \\\"warm, smoky, intense\\\" }, \\\"surface_and_reflection\\\": { \\\"base\\\": \\\"wet surface with liquid splash crown\\\", \\\"reflection_quality\\\": \\\"subtle reflective highlights\\\" } }\"}")
  req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/gpt_image_2/text_to_image", body)
  if err != nil {
    log.Fatal(err)
  }

  req.Header.Set("Authorization", "Bearer "+os.Getenv("RUNAPI_API_KEY"))
  req.Header.Set("Content-Type", "application/json")

  resp, err := http.DefaultClient.Do(req)
  if err != nil {
    log.Fatal(err)
  }
  defer resp.Body.Close()

  fmt.Println(resp.Status)
}
gpt-image-2 /api/v1/gpt_image_2/text_to_image Get API Key
IM
Image
Poster and Graphic Design gpt-image-2

Create a vertical launch poster for a fictional design confe

Create a vertical launch poster for a fictional design conference called 'FRAME 2026'. Large headline: 'FRAME 2026'. Subtitle: 'DESIGNING WITH MACHINE IMAGINATION'. Clean Swiss grid layout, off-white textured background, black typography, one red geometric accent shape, generous negative space, perfectly legible text, no extra words, no watermark. Aspect ratio 9:16.

View API Code
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "gpt-image-2",
  "prompt": "Create a vertical launch poster for a fictional design conference called 'FRAME 2026'. Large headline: 'FRAME 2026'. Subtitle: 'DESIGNING WITH MACHINE IMAGINATION'. Clean Swiss grid layout, off-white textured background, black typography, one red geometric accent shape, generous negative space, perfectly legible text, no extra words, no watermark. Aspect ratio 9:16."
}
JSON
IM
Image
Poster and Graphic Design gpt-image-2

A clean infographic titled 'HOW IMAGE PROMPTS WORK' with fiv

A clean infographic titled 'HOW IMAGE PROMPTS WORK' with five labeled steps arranged horizontally: 'Scene', 'Subject', 'Text', 'Composition', 'Constraints'. Flat editorial icons for each step, directional arrows between them, high contrast design, white background, readable sans-serif labels, consistent spacing throughout, no extra text, no watermark. 16:9 aspect ratio.

View API Code
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "gpt-image-2",
  "prompt": "A clean infographic titled 'HOW IMAGE PROMPTS WORK' with five labeled steps arranged horizontally: 'Scene', 'Subject', 'Text', 'Composition', 'Constraints'. Flat editorial icons for each step, directional arrows between them, high contrast design, white background, readable sans-serif labels, consistent spacing throughout, no extra text, no watermark. 16:9 aspect ratio."
}
JSON
IM
Image
Poster and Graphic Design gpt-image-2

A minimalist album cover with the title 'SOFT SIGNALS' in ce

A minimalist album cover with the title 'SOFT SIGNALS' in centered elegant serif typography, artist name 'MIRA VALE' in smaller tracking below, muted blue handmade paper texture background, a small silver line illustration of a radio tower centered between the text, elegant spacing throughout, no extra text, no logo. Square 1:1 format.

View API Code
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "gpt-image-2",
  "prompt": "A minimalist album cover with the title 'SOFT SIGNALS' in centered elegant serif typography, artist name 'MIRA VALE' in smaller tracking below, muted blue handmade paper texture background, a small silver line illustration of a radio tower centered between the text, elegant spacing throughout, no extra text, no logo. Square 1:1 format."
}
JSON
IM
Image
Poster and Graphic Design gpt-image-2

A bookstore window poster reading 'READ MORE SLOWLY' in larg

A bookstore window poster reading 'READ MORE SLOWLY' in large serif type with a smaller line 'SPRING READING WEEK' beneath it, warm evening street reflections visible in the glass surface, cream paper texture, all typography perfectly readable, no extra words, no watermark. 4:5 aspect ratio.

View API Code
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "gpt-image-2",
  "prompt": "A bookstore window poster reading 'READ MORE SLOWLY' in large serif type with a smaller line 'SPRING READING WEEK' beneath it, warm evening street reflections visible in the glass surface, cream paper texture, all typography perfectly readable, no extra words, no watermark. 4:5 aspect ratio."
}
JSON
IM
Image
Poster and Graphic Design gpt-image-2

Create a horizontal Chinese blockbuster movie poster for a f

Create a horizontal Chinese blockbuster movie poster for a fantasy adventure film titled '天机启明' with subtitle '失落的文明'. The poster features a dramatic ensemble cast composition with five to six realistic character headshots arranged in a pyramid formation. Behind them, a glowing ancient tower emits golden circular energy rings against a dramatic stormy sky. Burning ruins and traditional Chinese architecture visible in the middle ground. The title rendered in large stylized golden Chinese calligraphy. Format badges for 3D, IMAX, and Dolby visible at the bottom.

View API Code
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "gpt-image-2",
  "prompt": "Create a horizontal Chinese blockbuster movie poster for a fantasy adventure film titled '天机启明' with subtitle '失落的文明'. The poster features a dramatic ensemble cast composition with five to six realistic character headshots arranged in a pyramid formation. Behind them, a glowing ancient tower emits golden circular energy rings against a dramatic stormy sky. Burning ruins and traditional Chinese architecture visible in the middle ground. The title rendered in large stylized golden Chinese calligraphy. Format badges for 3D, IMAX, and Dolby visible at the bottom."
}
JSON
IM
Image
Poster and Graphic Design gpt-image-2

Science encyclopedia vertical card based on the theme of dee

Science encyclopedia vertical card based on the theme of deep-sea bioluminescent creatures. Beautiful main visual of a glowing anglerfish in the deep ocean. Detail close-up insets showing the bioluminescent organ structure. Rounded modular information sections with facts about depth range, diet, and size. Clear title hierarchy with the creature name prominent. Information-dense but not crowded layout, like a publishable museum card. Dark ocean blue background.

View API Code
curl -X POST https://runapi.ai/api/v1/gpt_image_2/text_to_image \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "gpt-image-2",
  "prompt": "Science encyclopedia vertical card based on the theme of deep-sea bioluminescent creatures. Beautiful main visual of a glowing anglerfish in the deep ocean. Detail close-up insets showing the bioluminescent organ structure. Rounded modular information sections with facts about depth range, diet, and size. Clear title hierarchy with the creature name prominent. Information-dense but not crowded layout, like a publishable museum card. Dark ocean blue background."
}
JSON
FAQ

Using gpt-image-2 prompts

What is %{model}?

%{model} is available through RunAPI as part of the unified model catalog. These prompts show practical input patterns that agents and backend services can reuse.

How do I use these prompts?

Copy any prompt and paste it into Claude Code, Codex, Cursor, or Windsurf after installing the RunAPI MCP Server. Developers can also copy the API example and send the prompt directly.

Do these prompts cost money to browse?

Browsing and copying prompt examples is free. Generation requests only cost money when you call a RunAPI model with your API key.

Can I adapt the prompts for production?

Yes. Treat each prompt as a starting point, then add your brand rules, output dimensions, safety constraints, and application-specific context before using it in production.