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
Illustration and 2D Art gpt-image-2

Professional character reference sheet for an original fanta

Professional character reference sheet for an original fantasy RPG character — a young female mage with silver hair and violet eyes wearing an ornate dark cloak with glowing rune patterns. Clean white background. Three-view turnaround showing front, side, and back. Row of facial expression variations: neutral, smiling, angry, surprised. Detailed costume and equipment breakdowns with callout lines. Color palette swatch row at the bottom. Brief world-building notes in clean typography. Organized grid layout, concept art style, high resolution. 16:9.

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": "Professional character reference sheet for an original fantasy RPG character — a young female mage with silver hair and violet eyes wearing an ornate dark cloak with glowing rune patterns. Clean white background. Three-view turnaround showing front, side, and back. Row of facial expression variations: neutral, smiling, angry, surprised. Detailed costume and equipment breakdowns with callout lines. Color palette swatch row at the bottom. Brief world-building notes in clean typography. Organized grid layout, concept art style, high resolution. 16:9."
}
JSON
IM
Image
Illustration and 2D Art gpt-image-2

Inside a museum exhibit titled 'Ancient Technology: The Desk

Inside a museum exhibit titled 'Ancient Technology: The Desktop Era', a programmer in a glass display case live-demonstrates coding on a CRT monitor while amazed schoolchildren press their faces against the glass. Exhibit placard reads: 'Homo Developerus (c. 2005) - Primitive human using keyboard-based input devices.' A second display case nearby shows a physical book labeled 'Stack Overflow - Print Edition, Vol. 1 of 4,827.' 2D cartoon illustration style, warm museum lighting, humorous and nostalgic tone. 16:9.

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": "Inside a museum exhibit titled 'Ancient Technology: The Desktop Era', a programmer in a glass display case live-demonstrates coding on a CRT monitor while amazed schoolchildren press their faces against the glass. Exhibit placard reads: 'Homo Developerus (c. 2005) - Primitive human using keyboard-based input devices.' A second display case nearby shows a physical book labeled 'Stack Overflow - Print Edition, Vol. 1 of 4,827.' 2D cartoon illustration style, warm museum lighting, humorous and nostalgic tone. 16:9."
}
JSON
IM
Image
Illustration and 2D Art gpt-image-2

Hand-drawn city food map of Chengdu with a bird's-eye-view i

Hand-drawn city food map of Chengdu with a bird's-eye-view illustrated base map, 12 hand-drawn food spot illustrations showing local dishes — mapo tofu, dan dan noodles, hot pot, rabbit heads — with handwritten labels in both Chinese and English, vine and chili pepper decorative border, title 'Chengdu Foodie Walking Map' in rounded hand-lettered typography, watercolor and colored pencil mixed media texture

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": "Hand-drawn city food map of Chengdu with a bird's-eye-view illustrated base map, 12 hand-drawn food spot illustrations showing local dishes — mapo tofu, dan dan noodles, hot pot, rabbit heads — with handwritten labels in both Chinese and English, vine and chili pepper decorative border, title 'Chengdu Foodie Walking Map' in rounded hand-lettered typography, watercolor and colored pencil mixed media texture"
}
JSON
IM
Image
Illustration and 2D Art gpt-image-2

A four-panel comic strip titled 'MORNING ROUTINE' — Panel 1:

A four-panel comic strip titled 'MORNING ROUTINE' — Panel 1: alarm clock ringing, character groaning under covers. Panel 2: character makes coffee with bleary eyes. Panel 3: character sits down at desk looking determined. Panel 4: character already fast asleep at the desk, coffee untouched. Warm minimal illustration style with expressive character design, readable title text, consistent character across all panels. 16:9.

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 four-panel comic strip titled 'MORNING ROUTINE' — Panel 1: alarm clock ringing, character groaning under covers. Panel 2: character makes coffee with bleary eyes. Panel 3: character sits down at desk looking determined. Panel 4: character already fast asleep at the desk, coffee untouched. Warm minimal illustration style with expressive character design, readable title text, consistent character across all panels. 16:9."
}
JSON
IM
Image
Illustration and 2D Art gpt-image-2

A two-panel comic about a small robot learning to paint — Pa

A two-panel comic about a small robot learning to paint — Panel 1: robot carefully studying a blank canvas with analytical scanning eyes, paint palette in mechanical hand. Panel 2: robot proudly displaying a messy but charming abstract painting with paint splattered on its chassis. Warm studio lighting, expressive robot body language, simple title 'FIRST ATTEMPT' below. 16:9.

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 two-panel comic about a small robot learning to paint — Panel 1: robot carefully studying a blank canvas with analytical scanning eyes, paint palette in mechanical hand. Panel 2: robot proudly displaying a messy but charming abstract painting with paint splattered on its chassis. Warm studio lighting, expressive robot body language, simple title 'FIRST ATTEMPT' below. 16:9."
}
JSON
IM
Image
Illustration and 2D Art gpt-image-2

Wuxia style swordswoman portrait, cold and sharp phoenix eye

Wuxia style swordswoman portrait, cold and sharp phoenix eyes, porcelain-white skin, long straight black hair wet and windswept across her face, soaked dark martial arts outfit clinging to her form, ancient sword held at her side with blue qi energy glow emanating from the blade, moonlit bamboo forest background with fog, 8K masterpiece quality, dramatic rim lighting from the moon. 9:16 vertical.

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": "Wuxia style swordswoman portrait, cold and sharp phoenix eyes, porcelain-white skin, long straight black hair wet and windswept across her face, soaked dark martial arts outfit clinging to her form, ancient sword held at her side with blue qi energy glow emanating from the blade, moonlit bamboo forest background with fog, 8K masterpiece quality, dramatic rim lighting from the moon. 9:16 vertical."
}
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.