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Seedream 5.0 Pro Text to Image API

bytedance/seedream-v5-pro/text-to-image

Generate high-resolution images from a text prompt, with accurate in-image text and crisp detail — the premium tier of Seedream 5.0.

0.09
OpenAPI

Model Input

Input

Text prompt describing the image to generate.

Output image dimensions as WxH pixels. Values at or below ~2.36 megapixels (e.g. 1024x1024, 1376x768) bill at the lower price tier; higher-resolution values (e.g. 2048x2048) bill at the premium tier.

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Model Output

Output

Generated image output
Generated in 140.533 seconds
Logs (1 lines)

Model Example Requests

Examples

Example output 1Example output 2Example output 3

Seedream 5.0 Pro Text to Image API

Seedream 5.0 Pro Text to Image is a text-to-image AI model by bytedance. On ModelRunner it runs through a REST API or via MCP from any AI assistant, at $0.09 per image.

POST https://queue.modelrunner.run/bytedance/seedream-v5-pro/text-to-image

cURL

# Submit a request to the queue. Input fields go at the top level of the
# body. The optional reserved "metadata" object holds your own flat string
# tags — stored on the request, never sent to the model; filter later with
# GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>.
curl -X POST https://queue.modelrunner.run/bytedance/seedream-v5-pro/text-to-image \
  -H "Authorization: Key $MRUN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "size": "1024x1024",
    "prompt": "A serene Japanese rock garden at dawn: a crimson maple tree beside a still koi pond, moss-covered stones, and a weath…",
    "metadata": {
      "project": "my-project"
    }
  }'
# → { "request_id": "...", "status_url": "...", "response_url": "..." }

# Poll status_url until "COMPLETED", then fetch the result
curl "https://queue.modelrunner.run/bytedance/seedream-v5-pro/text-to-image/requests/$REQUEST_ID/status" \
  -H "Authorization: Key $MRUN_API_KEY"
curl "https://queue.modelrunner.run/bytedance/seedream-v5-pro/text-to-image/requests/$REQUEST_ID" \
  -H "Authorization: Key $MRUN_API_KEY"

JavaScript

import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe("bytedance/seedream-v5-pro/text-to-image", {
  input: {
    "size": "1024x1024",
    "prompt": "A serene Japanese rock garden at dawn: a crimson maple tree beside a still koi pond, moss-covered stones, and a weath…"
  },
});
console.log(result);

Python

import os
import requests

headers = {"Authorization": f"Key {os.environ['MRUN_API_KEY']}"}

submitted = requests.post(
    "https://queue.modelrunner.run/bytedance/seedream-v5-pro/text-to-image",
    headers=headers,
    json={
      "size": "1024x1024",
      "prompt": "A serene Japanese rock garden at dawn: a crimson maple tree beside a still koi pond, moss-covered stones, and a weath…"
    },
).json()

# Poll submitted["status_url"] until "COMPLETED", then:
result = requests.get(submitted["response_url"], headers=headers).json()

Input parameters

NameTypeRequiredDescription
promptstringyesText prompt describing the image to generate.
sizeenumnoOutput image dimensions as WxH pixels. Values at or below ~2.36 megapixels (e.g. 1024x1024, 1376x768) bill at the lower price tier; higher-resolution values (e.g. 2048x2048) bill at the premium tier. Default: "1024x1024".

Machine-readable: OpenAPI schema · llms.txt

Use Seedream 5.0 Pro Text to Image from Claude & Cursor (MCP)

Point Claude Code, Claude Desktop, Cursor, or any MCP client at the ModelRunner MCP server and Seedream 5.0 Pro Text to Image becomes a tool your assistant can call directly — it authorizes via OAuth (no API key in config) and runs this model with the run_model tool using the endpoint bytedance/seedream-v5-pro/text-to-image.

MCP client config (Claude Desktop, Cursor)

{
  "mcpServers": {
    "modelrunner": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.modelrunner.run/mcp"]
    }
  }
}

Claude Code

claude mcp add --transport http modelrunner https://mcp.modelrunner.run/mcp

Then ask your assistant, for example: “Run bytedance/seedream-v5-pro/text-to-image on ModelRunner to generate image”. MCP setup guide.

Model Details

Model Details

Seedream 5.0 Pro Text to Image is the premium tier of the Seedream 5.0 image line, focused on creating images from a written prompt. Give it a text prompt and it renders sharp detail, accurate and legible in-image text, and coherent scenes with strong prompt following. Outputs range from roughly 1 up to ~4.2 megapixels (2K), so you can pick the resolution and aspect ratio that fit the job. Larger output sizes cost more per image.

## Best for - High-fidelity text-to-image from a written description - Rendering accurate, legible in-image text (posters, logos, UI mockups, ads) - Photorealistic scenes and product shots where detail and prompt accuracy matter - Concept art, illustration, and marketing visuals at up to 2K resolution - Premium-quality generation where detail matters more than speed or price

## Choose another model when - You want to edit, restyle, or composite an existing image from reference images — use `bytedance/seedream-v5-pro/edit` - You want the fastest, cheapest generation and can trade some quality — use the Lite tier `bytedance/seedream-v5/text-to-image` - You need several images from one call — this tier returns a single image per request - You need a video rather than a still image — use a text-to-video model

## Tips - `size` sets both resolution and aspect ratio; pick a ~1MP value (e.g. `1024x1024`, `1376x768`) for the lower price tier, or a 2K value (e.g. `2048x2048`) for maximum detail at the premium tier - Put any text you want rendered inside quotation marks in the prompt for the most accurate spelling - Describe subject, style, lighting, and composition explicitly — the model follows detailed prompts closely

To run via the ModelRunner JavaScript client: ```js import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe("bytedance/seedream-v5-pro/text-to-image", { input: { prompt: "a serene mountain lake at golden hour, photorealistic, sharp reflection", size: "1024x1024", }, }); ```