模型 PROMPTS

gpt-image-2 Prompts — 297 个精选示例

通过 RunAPI 使用 gpt-image-2 的示例。复制 prompt 后,可在 Claude Code、Codex、Cursor、Windsurf 或后端 API 中使用。

模型

gpt-image-2

模态
图像
提供方
OpenAI
Endpoint
Text To Image
查看模型详情和定价 →
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. 重启 Claude Code
3. 粘贴这个 prompt:生成一张图像:"{ "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. 重启 Codex
3. 粘贴这个 prompt:生成一张图像:"{ "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. 重启 Cursor
3. 粘贴这个 prompt:生成一张图像:"{ "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. 重启 Windsurf
3. 粘贴这个 prompt:生成一张图像:"{ "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 获取 API Key
IM
图像
Photography gpt-image-2

A 3x3 grid storyboard contact sheet comprised of nine candid...

A 3x3 grid storyboard contact sheet comprised of nine candid, cinematic movie stills showing a continuous sequence of a young man, approximately 20-25 years old. He has tousled brown hair and a youthful, expressive face, clean-shaven. Across all nine panels, he is consistently wearing a brown short-sleeved linen button-down shirt and is seated at a wooden dining table during a family dinner. The panels show varied natural actions: gesturing with his hands while animatedly talking, laughing, eating lasagna from a large dish, listening intently, and smiling. The environment is a warm, cozy home dining room with a wooden hutch filled with china and patterned wallpaper visible in the background. The lighting is soft, warm tungsten evening light creating natural shadows. The shots are a mix of medium angles and close-ups with a shallow depth of field, rendered with a film photography aesthetic and slight grain.

查看 API 代码
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 3x3 grid storyboard contact sheet comprised of nine candid, cinematic movie stills showing a continuous sequence of a young man, approximately 20-25 years old. He has tousled brown hair and a youthful, expressive face, clean-shaven. Across all nine panels, he is consistently wearing a brown short-sleeved linen button-down shirt and is seated at a wooden dining table during a family dinner. The panels show varied natural actions: gesturing with his hands while animatedly talking, laughing, eating lasagna from a large dish, listening intently, and smiling. The environment is a warm, cozy home dining room with a wooden hutch filled with china and patterned wallpaper visible in the background. The lighting is soft, warm tungsten evening light creating natural shadows. The shots are a mix of medium angles and close-ups with a shallow depth of field, rendered with a film photography aesthetic and slight grain."
}
JSON
IM
图像
Photography gpt-image-2

{ "objective": "Generate a hyper-realistic black and white...

{ "objective": "Generate a hyper-realistic black and white street fashion photograph with selective color accents.", "image_type": "photography", "prompt": { "subject": "A stylish, confident woman crossing a busy city intersection", "wardrobe": { "outerwear": "Oversized blazer in neutral tone", "innerwear": "Bright red fitted top (selective color)", "bottoms": "Loose tailored trousers in neutral tone", "accessories": [ "Bright red leather clutch in hand", "Bright red sunglasses" ] }, "action_motion": "Walking briskly toward the camera, hair flowing backward due to motion, blazer and trousers moving naturally", "scene": "Busy urban crosswalk with pedestrians and cars motion-blurred in the background", "perspective": "Frontal tracking shot at waist level", "style": [ "High-end street fashion", "Paparazzi aesthetic", "Editorial candid", "Dynamic movement photography" ], "visual_details": [ "Realistic fabric physics", "Detailed hair movement", "Sharp facial features", "Asphalt road texture", "Motion blur on background crowd", "Bokeh city lights" ], "mood": [ "Confident", "Cosmopolitan", "Urgent", "Powerful" ] }, "camera_and_composition": { "angle": "Waist-level", "framing": "Subject centered, background expanding outward with motion blur", "depth_of_field": "Shallow depth of field isolating the subject" }, "lighting": { "type": "Natural backlight with rim lighting", "contrast": "High contrast emphasizing silhouette and edges" }, "post_processing": { "color_mode": "Black and white with selective red color accents only on innerwear, sunglasses, and clutch bag", "effects": [ "Subtle lens flare", "Vintage film stock emulation", "High micro-contrast", "Film grain texture" ] }, "negative_prompt": [ "Posed studio look", "Empty street", "Static posture", "Low realism", "Full color image", "Overexposed highlights", "Flat lighting" ], "output_quality": { "resolution": "Ultra high resolution", "detail_level": "Maximum photorealism", "sharpness": "Crisp subject, soft background" } }

查看 API 代码
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": "{ \"objective\": \"Generate a hyper-realistic black and white street fashion photograph with selective color accents.\", \"image_type\": \"photography\", \"prompt\": { \"subject\": \"A stylish, confident woman crossing a busy city intersection\", \"wardrobe\": { \"outerwear\": \"Oversized blazer in neutral tone\", \"innerwear\": \"Bright red fitted top (selective color)\", \"bottoms\": \"Loose tailored trousers in neutral tone\", \"accessories\": [ \"Bright red leather clutch in hand\", \"Bright red sunglasses\" ] }, \"action_motion\": \"Walking briskly toward the camera, hair flowing backward due to motion, blazer and trousers moving naturally\", \"scene\": \"Busy urban crosswalk with pedestrians and cars motion-blurred in the background\", \"perspective\": \"Frontal tracking shot at waist level\", \"style\": [ \"High-end street fashion\", \"Paparazzi aesthetic\", \"Editorial candid\", \"Dynamic movement photography\" ], \"visual_details\": [ \"Realistic fabric physics\", \"Detailed hair movement\", \"Sharp facial features\", \"Asphalt road texture\", \"Motion blur on background crowd\", \"Bokeh city lights\" ], \"mood\": [ \"Confident\", \"Cosmopolitan\", \"Urgent\", \"Powerful\" ] }, \"camera_and_composition\": { \"angle\": \"Waist-level\", \"framing\": \"Subject centered, background expanding outward with motion blur\", \"depth_of_field\": \"Shallow depth of field isolating the subject\" }, \"lighting\": { \"type\": \"Natural backlight with rim lighting\", \"contrast\": \"High contrast emphasizing silhouette and edges\" }, \"post_processing\": { \"color_mode\": \"Black and white with selective red color accents only on innerwear, sunglasses, and clutch bag\", \"effects\": [ \"Subtle lens flare\", \"Vintage film stock emulation\", \"High micro-contrast\", \"Film grain texture\" ] }, \"negative_prompt\": [ \"Posed studio look\", \"Empty street\", \"Static posture\", \"Low realism\", \"Full color image\", \"Overexposed highlights\", \"Flat lighting\" ], \"output_quality\": { \"resolution\": \"Ultra high resolution\", \"detail_level\": \"Maximum photorealism\", \"sharpness\": \"Crisp subject, soft background\" } }"
}
JSON
IM
图像
Photography gpt-image-2

Create a hyper-realistic, stylish vertical poster featuring...

Create a hyper-realistic, stylish vertical poster featuring a smartphone lying on a table, transformed into a hockey rink. The screen resembles cracked ice with deep fissures, while tiny hockey players compete in an intense game Use diffused daylight with elegant reflections and refractions to enhance depth. Add realistic details like fingerprints, smudges, and subtle scratches on the phone's surface for authenticity. Craft a dynamic perspective with an intriguing camera angle-slightly tilted for dramatic effect. The image should look like a high-quality DSLR photograph, with sharp focus, rich textures, and cinematic lighting to amplify the surreal yet lifelike atmosphere

查看 API 代码
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 hyper-realistic, stylish vertical poster featuring a smartphone lying on a table, transformed into a hockey rink. The screen resembles cracked ice with deep fissures, while tiny hockey players compete in an intense game Use diffused daylight with elegant reflections and refractions to enhance depth. Add realistic details like fingerprints, smudges, and subtle scratches on the phone's surface for authenticity. Craft a dynamic perspective with an intriguing camera angle-slightly tilted for dramatic effect. The image should look like a high-quality DSLR photograph, with sharp focus, rich textures, and cinematic lighting to amplify the surreal yet lifelike atmosphere"
}
JSON
IM
图像
Photography gpt-image-2

A high-quality, candid street photography shot of a stylish...

A high-quality, candid street photography shot of a stylish young woman with short wavy brown hair. She is wearing a maroon cardigan, oversized beige denim cargo pants, and a maroon baseball cap. She has large white over-ear headphones around her ears and a black quilted shoulder bag with a small plush dog keychain hanging from it.Same face as in reference

查看 API 代码
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 high-quality, candid street photography shot of a stylish young woman with short wavy brown hair. She is wearing a maroon cardigan, oversized beige denim cargo pants, and a maroon baseball cap. She has large white over-ear headphones around her ears and a black quilted shoulder bag with a small plush dog keychain hanging from it.Same face as in reference"
}
JSON
IM
图像
Photography gpt-image-2

description: "A clean, aesthetic 3x3 collage portrait showca...

description: "A clean, aesthetic 3x3 collage portrait showcasing different men's hairstyles. The same young man is captured in each frame, positioned in consistent lighting and pose, creating a style comparison grid.", "subject": { "type": "young man", "age": "early 20s", "skin_tone": "medium with smooth texture", "facial_features": "sharp jawline, well-groomed beard stubble, symmetrical face", "expression": "neutral and confident" }, "hairstyles": [ "clean shaved buzz cut", "slicked back classic hairstyle", "medium wavy long hair", "short textured fringe", "voluminous messy hairstyle", "man bun", "cornrow braids", "side swept modern fade", "tight curly textured cut" ], "environment": { "location": "outdoor courtyard with white architecture arches", "lighting": "soft sunset golden-hour lighting", "background": "slightly blurred but clean and minimal" }, "camera": { "shot": "shoulder-level portrait", "angle": "eye-level", "lens": "standard lens (50mm)", "composition": "consistent framing for all nine shots" }, "wardrobe": { "top": "plain fitted white t-shirt", "style": "minimal, clean, modern" }, "mood": [ "stylish", "fresh", "groomed", "aesthetic" ] }

查看 API 代码
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": "description: \"A clean, aesthetic 3x3 collage portrait showcasing different men's hairstyles. The same young man is captured in each frame, positioned in consistent lighting and pose, creating a style comparison grid.\", \"subject\": { \"type\": \"young man\", \"age\": \"early 20s\", \"skin_tone\": \"medium with smooth texture\", \"facial_features\": \"sharp jawline, well-groomed beard stubble, symmetrical face\", \"expression\": \"neutral and confident\" }, \"hairstyles\": [ \"clean shaved buzz cut\", \"slicked back classic hairstyle\", \"medium wavy long hair\", \"short textured fringe\", \"voluminous messy hairstyle\", \"man bun\", \"cornrow braids\", \"side swept modern fade\", \"tight curly textured cut\" ], \"environment\": { \"location\": \"outdoor courtyard with white architecture arches\", \"lighting\": \"soft sunset golden-hour lighting\", \"background\": \"slightly blurred but clean and minimal\" }, \"camera\": { \"shot\": \"shoulder-level portrait\", \"angle\": \"eye-level\", \"lens\": \"standard lens (50mm)\", \"composition\": \"consistent framing for all nine shots\" }, \"wardrobe\": { \"top\": \"plain fitted white t-shirt\", \"style\": \"minimal, clean, modern\" }, \"mood\": [ \"stylish\", \"fresh\", \"groomed\", \"aesthetic\" ] }"
}
JSON
IM
图像
Photography gpt-image-2

Higgsfield just dropped GPT Image 1.5 — I tried the "impossi...

Higgsfield just dropped GPT Image 1.5 — I tried the "impossible" test everyone thought would fail: 1⃣ Pure anime illustration only 2⃣ Extract every clothing item while keeping anime style 3⃣ Take those flat 2D clothes 4⃣ Dress a 100% photorealistic girl with them No LoRA. No training. Just one simple prompt. Result: pleats fold like real fabric, cardigan has actual weight, socks compress naturally. GPT Image 1.5 doesn’t just copy styles — it truly understands clothing physics and materials. Anime uniform on a real human. For real. My brain is broken 🤯✨ #Higgsfield #gptimage

查看 API 代码
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": "Higgsfield just dropped GPT Image 1.5 — I tried the \"impossible\" test everyone thought would fail: 1⃣ Pure anime illustration only 2⃣ Extract every clothing item while keeping anime style 3⃣ Take those flat 2D clothes 4⃣ Dress a 100% photorealistic girl with them No LoRA. No training. Just one simple prompt. Result: pleats fold like real fabric, cardigan has actual weight, socks compress naturally. GPT Image 1.5 doesn’t just copy styles — it truly understands clothing physics and materials. Anime uniform on a real human. For real. My brain is broken 🤯✨ #Higgsfield #gptimage"
}
JSON
常见问题

使用 gpt-image-2 prompts

%{model} 是什么?

%{model} 是 RunAPI 统一模型目录中的模型。这些 prompts 展示了 agent 和后端服务可以复用的实际输入模式。

如何使用这些 prompts?

安装 RunAPI MCP Server 后,复制任意 prompt 并粘贴到 Claude Code、Codex、Cursor 或 Windsurf。开发者也可以复制 API 示例直接调用。

浏览这些 prompts 要付费吗?

浏览和复制 prompt 示例是免费的。只有当你使用 API key 调用 RunAPI 模型生成内容时,才会产生费用。

这些 prompts 可以用于生产环境吗?

可以。把每个 prompt 当作起点,再补充品牌规则、输出尺寸、安全约束和你的业务上下文。