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
infographic gpt-image-2

Infographic — coffee brewing methods compared

Clean infographic comparing four coffee brewing methods side by side: French Press, Pour Over, Espresso, and Cold Brew. Each method is represented by a simplified cross-section diagram of its equipment showing water flow and coffee grounds interaction. Below each diagram: brew time, grind size, water temperature, and strength rating shown as icon-based data points. The layout is a single horizontal row on a cream background. Color coding uses warm browns and subtle orange accents. Typography is modern sans-serif. The overall design is editorial and information-dense without feeling cluttered.

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": "Clean infographic comparing four coffee brewing methods side by side: French Press, Pour Over, Espresso, and Cold Brew. Each method is represented by a simplified cross-section diagram of its equipment showing water flow and coffee grounds interaction. Below each diagram: brew time, grind size, water temperature, and strength rating shown as icon-based data points. The layout is a single horizontal row on a cream background. Color coding uses warm browns and subtle orange accents. Typography is modern sans-serif. The overall design is editorial and information-dense without feeling cluttered."
}
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.