Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain.
imagen-4/api/v1/imagen_4/text_to_image
RUN DETAILS
Model
imagen-4
Provider
Google
Service
Imagen 4
Endpoint
Text To Image
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. Restart Claude Code
3. Paste this prompt: Generate an image: "Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain."
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate an image: "Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain."
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate an image: "Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain."
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate an image: "Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain."
curl -X POST https://runapi.ai/api/v1/imagen_4/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "imagen-4",
"prompt": "Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain."
}
JSON
import { Imagen4Client } from "@runapi.ai/imagen-4";
const client = new Imagen4Client({
apiKey: process.env.RUNAPI_API_KEY,
});
const result = await client.textToImage.run({
"model": "imagen-4",
"prompt": "Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain."
});
console.log(result.id);
require "runapi/imagen_4"
client = RunApi::Imagen4::Client.new
result = client.text_to_image.run(
model: "imagen-4",
prompt: "Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain."
)
puts result.id
package main
import (
"context"
"fmt"
"log"
"net/http"
"os"
"strings"
)
func main() {
body := strings.NewReader("{\"model\":\"imagen-4\",\"prompt\":\"Editorial fashion photo of an African-American man in a black leather shearling jacket, leaning into a beige vintage car from the outside. The scene is viewed from inside the car looking out through the passenger window. Sharp shadows, clean directional light, and cinematic framing. A desert landscape stretches out behind him. Moody atmosphere. 35mm film look with subtle grain.\"}")
req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/imagen_4/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)
}
A fluffy white Persian cat with bright blue eyes sitting gracefully on a sunlit windowsill, soft morning light streaming through lace curtains creating gentle dappled shadows, warm golden tones, shallow depth of field with sharp focus on the cat's face, photorealistic, shot on medium format camera
curl -X POST https://runapi.ai/api/v1/imagen_4/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "imagen-4",
"prompt": "A fluffy white Persian cat with bright blue eyes sitting gracefully on a sunlit windowsill, soft morning light streaming through lace curtains creating gentle dappled shadows, warm golden tones, shallow depth of field with sharp focus on the cat's face, photorealistic, shot on medium format camera"
}
JSON
Vibrant product-on-moss hero shot for an eco sneaker brand. A single running shoe placed on a bed of fresh green moss, soft morning light filtering through trees above, minimal composition, forest green and cream color palette, natural outdoor product photography, 4:5 aspect ratio, no text.
curl -X POST https://runapi.ai/api/v1/imagen_4/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "imagen-4",
"prompt": "Vibrant product-on-moss hero shot for an eco sneaker brand. A single running shoe placed on a bed of fresh green moss, soft morning light filtering through trees above, minimal composition, forest green and cream color palette, natural outdoor product photography, 4:5 aspect ratio, no text."
}
JSON
35mm film photograph of a floating island suspended above the Moscow skyline, dramatic cumulus clouds surrounding it, cinematic golden hour lighting, vintage aesthetic with warm color tones, subtle film grain texture, architectural fantasy concept
Historically informed oil-painting-style scene of an ancient Roman marketplace at midday. Wide angle showing a colonnade with merchants, shoppers in period-accurate togas and tunics, baskets of goods, terracotta pottery. Warm Mediterranean sunlight creating defined shadows under the columns. Clear focal areas drawing the eye from foreground commerce to background architecture. 3:2 aspect ratio, no text.
curl -X POST https://runapi.ai/api/v1/imagen_4/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "imagen-4",
"prompt": "Historically informed oil-painting-style scene of an ancient Roman marketplace at midday. Wide angle showing a colonnade with merchants, shoppers in period-accurate togas and tunics, baskets of goods, terracotta pottery. Warm Mediterranean sunlight creating defined shadows under the columns. Clear focal areas drawing the eye from foreground commerce to background architecture. 3:2 aspect ratio, no text."
}
JSON
Environmental portrait of an elderly Japanese woodworker in his cluttered workshop. He holds a hand plane (kanna) at chest height, examining its blade with quiet concentration. Late afternoon sunlight enters through a small dusty window, catching wood shavings suspended in the air. His hands are weathered and precise. Shallow depth of field isolates him from shelves of chisels and saws behind him. Natural color palette dominated by warm wood tones. Documentary photography style, no posing, candid moment.
curl -X POST https://runapi.ai/api/v1/imagen_4/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "imagen-4",
"prompt": "Environmental portrait of an elderly Japanese woodworker in his cluttered workshop. He holds a hand plane (kanna) at chest height, examining its blade with quiet concentration. Late afternoon sunlight enters through a small dusty window, catching wood shavings suspended in the air. His hands are weathered and precise. Shallow depth of field isolates him from shelves of chisels and saws behind him. Natural color palette dominated by warm wood tones. Documentary photography style, no posing, candid moment."
}
JSON
FAQ
Using this imagen-4 prompt
How do I copy this prompt safely?
Use the copy button beside the full prompt block. It copies only the prompt text, not surrounding page labels, so you can paste it into an agent instruction, a JSON request body, or your own prompt library.
Why does the detail page show parameters?
Some prompts were collected with saved generation settings such as aspect ratio, duration, or voice controls. When parameters exist, the page lists them separately so you can reuse the prompt text and the structured settings together.
Which endpoint should I call?
Use the endpoint path shown in the API code block. The path is generated from the prompt's RunAPI service and endpoint name, then rendered as the public API URL used by curl and SDK examples.
Can I use this prompt in an agent instead of code?
Yes. Pick Claude Code, Codex, Cursor, or Windsurf in the tab switcher, install the RunAPI MCP Server, and paste the generated instruction. The instruction includes the full prompt text.