bytedance/seedream-v5.0-flash/text-to-image

text-to-image

Seedream v5.0 Flash Text-to-Image API by ByteDance

bytedance/seedream-v5.0-flash/text-to-image

Text-to-image

Dola-Seedream-5.0-flash, ByteDance's high-speed, cost-optimized image generation model built for instant creation. Generates a single image from a text prompt in seconds at 1K, 1.5K, or 2K - well suited to latency-sensitive scenarios such as mobile assistant apps, UGC content creation, and bulk-scale content production.

Compare models

Seedream v5.0 Flash Text-to-Image is developed by ByteDance. Atlas Cloud (operated by Atlas Cloud AI LLC) provides access to it and does not own it. All trademarks belong to their respective owners.

INPUT

Prompt *

Size

Output format

OUTPUT

Idle

Your generated images will appear here

Configure your settings and click Run to get started

Your request will cost $0.018 per run. For $10 you can run this model approximately 555 times.

Here's what you can do next:

Image-to-Video Image-to-Image

Parameters

Code Example
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "bytedance/seedream-v5.0-flash/text-to-image",  # Required. model name
    "enable_base64_output": False,  # If enabled, the output will be encoded into a BASE64 string instead of a URL
    "prompt": "A beautiful landscape with mountains and lake",  # Required. The positive prompt for the generation
    "size": "2048*2048",  # Output image size in 'WIDTH*HEIGHT' pixels, chosen from the official 2K and 1
    "output_format": "jpeg",  # Output image file format. options: jpeg | png
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] == "completed":
            print("Generated image:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

image_url = check_status()

Install

Install the required package for your language.

pip install requests

Authentication

All API requests require authentication via an API key. You can get your API key from the Atlas Cloud dashboard.

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP Headers

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Keep your API key secure

Never expose your API key in client-side code or public repositories. Use environment variables or a backend proxy instead.

Submit a request

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Submit a Request

Submit an asynchronous generation request. The API returns a prediction ID that you can use to check the status and retrieve the result.

POST/api/v1/model/generateImage

Request Body

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "bytedance/seedream-v5.0-flash/text-to-image",
    "prompt": "A beautiful landscape with mountains and lake"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

Response

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

Check Status

Poll the prediction endpoint to check the current status of your request.

GET/api/v1/model/prediction/{prediction_id}

Polling Example

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Status Values

processingThe request is still being processed.

completedGeneration is complete. Outputs are available.

succeededGeneration succeeded. Outputs are available.

failedGeneration failed. Check the error field.

Completed Response

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Upload Files

Upload files to Atlas Cloud storage and get a URL you can use in your API requests. Use multipart/form-data to upload.

POST/api/v1/model/uploadMedia

Upload Example

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Response

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

The following parameters are accepted in the request body.

Total: 5Required: 2Optional: 3

modelstringrequired

model name

Default: "bytedance/seedream-v5.0-flash/text-to-image"

enable_base64_outputboolean

If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.

Default: false

promptstringrequired

The positive prompt for the generation. Recommended length: under 600 English words.

sizestring

Output image size in 'WIDTH*HEIGHT' pixels, chosen from the official 2K and 1.5K presets. Every image bills the same flat price regardless of size.

Default: "2048*2048"

2048*20482368*17761776*23682816*15841584*28162496*16641664*24963136*13441536*15361792*13441344*17922048*11521152*20481872*12481248*18722352*1008

output_formatstring

Output image file format. Seedream v5.0 Flash supports both JPEG and PNG output.

Default: "jpeg"

jpegpng

Example Request Body

{
  "model": "bytedance/seedream-v5.0-flash/text-to-image",
  "enable_base64_output": false,
  "prompt": "A beautiful landscape",
  "size": "2048*2048",
  "output_format": "jpeg"
}

Output Schema

The API returns a prediction response with the generated output URLs.

codeinteger

Status code of the call; 200 on success.

messagestring

Status message of the call.

dataobject

The prediction: id, model, status, outputs, urls and created_at. Poll GET /api/v1/model/prediction/{request_id} with data.id until status is completed or failed.

Example Response

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills integrates 400+ AI models directly into your AI coding assistant. One command to install, then use natural language to generate images, videos, and chat with LLMs.

Supported Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ supported clients

Install

npx skills add AtlasCloudAI/atlas-cloud-skills

Setup API Key

Get your API key from the Atlas Cloud dashboard and set it as an environment variable.

export ATLASCLOUD_API_KEY="your-api-key-here"

Capabilities

Once installed, you can use natural language in your AI assistant to access all Atlas Cloud models.

Image GenerationGenerate images with models like Nano Banana 2, Z-Image, and more.

Video CreationCreate videos from text or images with Kling, Vidu, Veo, etc.

LLM ChatChat with Qwen, DeepSeek, and other large language models.

Media UploadUpload local files for image editing and image-to-video workflows.

Learn more

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server connects your IDE with 400+ AI models via the Model Context Protocol. Works with any MCP-compatible client.

Supported Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ supported clients

Install

npx -y atlascloud-mcp

Configuration

Add the following configuration to your IDE's MCP settings file.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Available Tools

atlas_generate_imageGenerate images from text prompts.

atlas_generate_videoCreate videos from text or images.

atlas_chatChat with large language models.

atlas_list_modelsBrowse 400+ available AI models.

atlas_quick_generateOne-step content creation with auto model selection.

atlas_upload_mediaUpload local files for API workflows.

Learn more

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "bytedance/seedream-v5.0-flash/text-to-image"
          },
          "enable_base64_output": {
            "default": false,
            "description": "If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.",
            "disabled": true,
            "type": "boolean"
          },
          "prompt": {
            "description": "The positive prompt for the generation. Recommended length: under 600 English words.",
            "type": "string",
            "x-rows": 10,
            "x-ui-component": "textarea"
          },
          "size": {
            "default": "2048*2048",
            "description": "Output image size in 'WIDTH*HEIGHT' pixels, chosen from the official 2K and 1.5K presets. Every image bills the same flat price regardless of size.",
            "enum": [
              "2048*2048",
              "2368*1776",
              "1776*2368",
              "2816*1584",
              "1584*2816",
              "2496*1664",
              "1664*2496",
              "3136*1344",
              "1536*1536",
              "1792*1344",
              "1344*1792",
              "2048*1152",
              "1152*2048",
              "1872*1248",
              "1248*1872",
              "2352*1008"
            ],
            "type": "string"
          },
          "output_format": {
            "default": "jpeg",
            "description": "Output image file format. Seedream v5.0 Flash supports both JPEG and PNG output.",
            "enum": [
              "jpeg",
              "png"
            ],
            "type": "string"
          }
        },
        "required": [
          "model",
          "prompt"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "size",
          "output_format",
          "enable_base64_output"
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "code": {
            "type": "integer",
            "description": "Status code of the call; 200 on success."
          },
          "message": {
            "type": "string",
            "description": "Status message of the call."
          },
          "data": {
            "type": "object",
            "description": "The prediction: id, model, status, outputs, urls and created_at. Poll GET /api/v1/model/prediction/{request_id} with data.id until status is completed or failed.",
            "allOf": [
              {
                "$ref": "#/components/schemas/PredictionData"
              }
            ]
          }
        }
      },
      "PredictionData": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., \"2023-04-01T12:34:56.789Z\").",
            "format": "date-time",
            "type": "string"
          },
          "id": {
            "description": "Unique identifier for the prediction, the ID of the prediction to get.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated content (empty when status is not completed).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  },
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API - bytedance/seedream-v5.0-flash/text-to-image",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          }
        },
        "responses": {
          "200": {
            "description": "The request status.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            }
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "type": "string",
              "description": "Request ID"
            }
          }
        ],
        "responses": {
          "200": {
            "description": "Result of the request.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            }
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM-Friendly Prompt Template

# bytedance/seedream-v5.0-flash/text-to-image

> Dola-Seedream-5.0-flash, ByteDance's high-speed, cost-optimized image generation model built for instant creation. Generates a single image from a text prompt in seconds at 1K, 1.5K, or 2K - well suited to latency-sensitive scenarios such as mobile assistant apps, UGC content creation, and bulk-scale content production.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `bytedance/seedream-v5.0-flash/text-to-image`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"bytedance/seedream-v5.0-flash/text-to-image"`

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation. Recommended length: under 600 English words.

- **`size`** (`string`, _optional_):
  Output image size in 'WIDTH*HEIGHT' pixels, chosen from the official 2K and 1.5K presets. Every image bills the same flat price regardless of size.
  - Default: `"2048*2048"`
  - Options: "2048*2048", "2368*1776", "1776*2368", "2816*1584", "1584*2816", "2496*1664", "1664*2496", "3136*1344", "1536*1536", "1792*1344", "1344*1792", "2048*1152", "1152*2048", "1872*1248", "1248*1872", "2352*1008"

- **`output_format`** (`string`, _optional_):
  Output image file format. Seedream v5.0 Flash supports both JPEG and PNG output.
  - Default: `"jpeg"`
  - Options: "jpeg", "png"

- **`enable_base64_output`** (`boolean`, _optional_):
  If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "model": "bytedance/seedream-v5.0-flash/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "bytedance/seedream-v5.0-flash/text-to-image",
  "prompt": "",
  "size": "2048*2048",
  "output_format": "jpeg",
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`code`** (`integer`, _optional_):
  Status code of the call; 200 on success.

- **`message`** (`string`, _optional_):
  Status message of the call.

- **`data`** (`object`, _optional_):
  The prediction: id, model, status, outputs, urls and created_at. Poll GET /api/v1/model/prediction/{request_id} with data.id until status is completed or failed.



**Example Response**:

```json
{
  "code": 0,
  "message": "",
  "data": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "bytedance/seedream-v5.0-flash/text-to-image",
  "prompt": "",
  "size": "2048*2048",
  "output_format": "jpeg",
  "enable_base64_output": false
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/bytedance/seedream-v5.0-flash/text-to-image)

A solitary figure standing on a dramatic cliff above a vast stormy ocean, enormous waves crashing against black volcanic rocks below, seabirds flying through the wind, sunlight breaking through heavy clouds over the horizon, powerful sense of freedom and solitude, cinematic storytelling, epic composition, atmospheric haze, natural lighting, anamorphic lens, photorealistic, 8K

1. Introduction

Seedream 5.0 Flash (Dola-Seedream-5.0-flash) is ByteDance's high-speed, cost-optimized member of the Seedream 5.0 image generation family, added in September 2026 (upstream model version dola-seedream-5-0-flash-260915). This README covers the API model identifier:

bytedance/seedream-v5.0-flash/text-to-image

Seedream 5.0 Flash shares Seedream 5.0 Pro's request contract, resolution envelope, and multilingual prompt support, but is tuned for latency and volume: a single 2K image typically completes in 10–20 seconds. ByteDance positions Dola-Seedream-5.0-flash for instant creation: a high-speed, cost-optimized model covering text-to-image generation, single- and multi-reference image workflows, precision editing, and layer decomposition, aimed at latency-sensitive scenarios such as mobile assistant applications, UGC content creation, and bulk-scale content production. (BytePlus ModelArk)

2. Key Features & Innovations

Fast Single-Image Generation: Returns one image per request, typically in 10–20 seconds at 2K and faster at 1K/1.5K, without a slow deep-thinking pass — well suited to interactive tools and on-demand pipelines.
Pro-Class Resolution Envelope: Output from 921,600 (1280×720) to 4,624,220 total pixels with any aspect ratio from 1:16 to 16:1, including official 2K presets such as 2048×2048, 2816×1584 (16:9), and 3136×1344 (21:9).
Multilingual Prompts: Beyond Chinese and English, prompts are understood in Russian, Arabic, Filipino, Thai, Turkish, Korean, Malay, Spanish, Portuguese, Indonesian, French, German, Vietnamese, and Japanese.
Clean Typography: Inherits the Seedream 5.0 family's text-rendering strength for signage, posters, and labels rendered directly into the image.
PNG and JPEG Output: Choose lossless PNG for design handoff or compact JPEG for web delivery; results are returned as hosted URLs or Base64.

3. Model Architecture & Technical Details

Seedream 5.0 Flash is built on the Seedream 5.0 family's multimodal transformer architecture — vision encoders coupled with a diffusion-based image decoder — with an inference path optimized for speed. Automatic prompt optimization runs in standard mode; the family's fast optimization mode and the ability to switch off prompt thinking are Pro-only controls, since Flash is already tuned for low latency.

Size is selected either by explicit WIDTH*HEIGHT (total pixels within [921,600, 4,624,220], aspect ratio within [1/16, 16]) or by the tier keywords 1K, 1.5K, and 2K, in which case the model infers the aspect ratio from the prompt. Sequential (multi-image) generation and streaming output are not supported: every request produces exactly one image.

4. Performance Highlights

Public arena rankings for the Flash snapshot are not yet available; its position in the Seedream 5.0 family:

Model	Developer	Output Range	Reference Images	Typical Latency (2K)
Seedream 5.0 Flash	ByteDance	1K–2K	up to 10	10–20 s
Seedream 5.0 Pro	ByteDance	1K–2K	up to 10	slower with prompt thinking enabled
Seedream 5.0 Lite	ByteDance	2K–4K	up to 14	—

Flash keeps Pro's single-image discipline and output envelope while cutting generation time, making it the default pick when throughput and responsiveness matter more than squeezing the last increment of per-image quality.

5. Intended Use & Applications

Mobile Assistant Applications: Instant image generation inside chat and assistant apps, where every second of latency is felt by the user.
UGC Content Creation: Fast, on-demand visuals for user-generated content platforms — avatars, posts, stickers, and creative prompts at interactive speed.
Bulk-Scale Content Production: Social posts, thumbnails, ad variations, and catalog imagery generated at scale with fast turnaround at any resolution.
Rapid Concept Exploration: Fast iteration on composition, style, and copy before committing a final render.
Localized Marketing Visuals: Multilingual prompts for regional campaigns, with text rendered directly into posters and banners.
E-Commerce Imagery: Product scenes and lifestyle shots at 2K for listing pages and advertising.

Seedream v5.0 Flash Text-to-Image API by ByteDance

INPUT

OUTPUT

Parameters

Code Example

Install

Authentication

HTTP Headers

Submit a request

Submit a Request

Request Body

Response

Check Status

Polling Example

Status Values

Completed Response

Upload Files

Upload Example

Response

Input Schema

Example Request Body

Output Schema

Example Response

Atlas Cloud Skills

Supported Clients

Install

Setup API Key

Capabilities

MCP Server

Supported Clients

Install

Configuration

Available Tools

API Schema

LLM-Friendly Prompt Template

1. Introduction

2. Key Features & Innovations

3. Model Architecture & Technical Details

4. Performance Highlights

5. Intended Use & Applications

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One API for All Media AI.

INPUT

OUTPUT

Parameters

Code Example

Install

Authentication

HTTP Headers

Submit a request

Submit a Request

Request Body

Response

Check Status

Polling Example

Status Values

Completed Response

Upload Files

Upload Example

Response

Input Schema

Example Request Body

Output Schema

Example Response