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

Image

Sci-Fi and Concept Art gpt-image-2

Cinematic first frame for an image-to-video clip: a lone ast

Cinematic first frame for an image-to-video clip: a lone astronaut standing at the edge of a glowing desert crater at dawn, space suit cape and dust particles ready to move in wind, strong foreground silhouette against the luminous crater, clear depth layers from foreground rocks to middle-ground crater to distant mountain horizon, warm orange horizon light fading to deep blue sky above, no text, no watermark. 16:9.

/api/v1/gpt_image_2/text_to_image

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": "Cinematic first frame for an image-to-video clip: a lone astronaut standing at the edge of a glowing desert crater at dawn, space suit cape and dust particles ready to move in wind, strong foreground silhouette against the luminous crater, clear depth layers from foreground rocks to middle-ground crater to distant mountain horizon, warm orange horizon light fading to deep blue sky above, no text, no watermark. 16:9."
}
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.