# Bytedance Doubao Seedream 5.0 (Build 260128) — Text To Image

> Use ByteDance Seedream 5.0 Lite API on GPTProto for $0.0298 per image—about 15% below the displayed market rate. Compare Seedream 5.0 Lite vs 4.5, check model IDs, and generate with one shared API balance.

## Overview

- **Endpoint**: `POST https://gptproto.com/api/v3/doubao/doubao-seedream-5-0-260128/text-to-image`
- **Result URL**: `GET https://gptproto.com/api/v3/predictions/{result_id}/result` — the submit response also returns the authoritative URL in `data.urls.get`
- **Model ID**: `doubao-seedream-5-0-260128`
- **Vendor**: Bytedance
- **Scene**: `text-to-image`
- **Category**: text-to-image
- **Modalities**: input text → output image
- **Playground**: https://gptproto.com/model/bytedance/doubao-seedream-5-0-260128
- **API documentation**: https://docs.gptproto.com/docs/allapi/Doubao/doubao-seedream-5-0-260128/gptproto-format/text-to-image
- **Other scenes of this model**: `image-edit` — same auth, different endpoint path and input schema

## Authentication

Every request needs a GPTProto API key in the `Authorization` header. Create one at https://gptproto.com/dashboard/api-key, then export it:

```bash
export GPTPROTO_API_KEY="your-api-key"
```

Header: `Authorization: Bearer $GPTPROTO_API_KEY` (plus `Content-Type: application/json` on POST).

## Pricing

Platform price by tier (USD, already includes the GPTProto discount):

- **1** — $0.0298 per run
- **2** — $0.0595 per run
- **3** — $0.0892 per run
- **4** — $0.119 per run
- **5** — $0.1487 per run
- **6** — $0.1785 per run
- **7** — $0.2082 per run
- **8** — $0.238 per run
- **9** — $0.2677 per run
- **10** — $0.2975 per run

Price range: $0.0298 – $0.2975 per generation.

Prices may change. The model page always shows the live price: https://gptproto.com/model/bytedance/doubao-seedream-5-0-260128

## API Information

The API is asynchronous: POST the endpoint to create a prediction, then poll its result URL until `status` is `completed` or `failed`.

### Input Schema

The endpoint accepts the following JSON body parameters:

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation.

- **`size`** (`integer`, _optional_):
  - Default: `2048x2048`

- **`enable_base64_output`** (`enum`, _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`
  - Options: true, false

- **`enable_sync_mode`** (`enum`, _optional_):
  If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.
  - Default: `false`
  - Options: true, false

**Required Parameters Example**:

```json
{
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle"
}
```

**Full Example**:

```json
{
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
  "size": "2048x2048",
  "enable_base64_output": false,
  "enable_sync_mode": false
}
```

### Output Schema

Both submit and poll return the same envelope:

- **`data.id`** (`string`): Prediction id. Use it as `result_id` when polling for the result.
- **`data.status`** (`string`): One of `created`, `running`, `completed`, `failed`. See Status Values below.
- **`data.outputs`** (`array of string`): Generated files. Empty until `status` is `completed`; then it holds the output URLs (or base64 strings when the model exposes a base64 option).
- **`data.urls.get`** (`string`): Authoritative result URL for this prediction. Prefer it over building the poll URL yourself.
- **`data.error`** (`string | null`): Failure reason when `status` is `failed`, otherwise `null`.
- **`data.executionTime`** (`integer`): Total processing time in milliseconds.
- **`data.timings.inference`** (`integer`): Model inference time in milliseconds.
- **`data.hasNsfwContents`** (`array of boolean`): Per-output moderation flags.
- **`message`** (`string`): `success` on a normal response, otherwise the error message.
- **`code`** (`integer`): Business status code. `200` means the request was accepted.

**Example Response — submit (task accepted)**:

```json
{
  "data": {
    "id": "pred_example_01",
    "model": "doubao-seedream-5-0-260128",
    "outputs": [],
    "urls": {
      "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result"
    },
    "hasNsfwContents": [],
    "status": "created",
    "createdAt": "2026-01-01T12:00:00Z",
    "executionTime": 0,
    "timings": {
      "inference": 0
    }
  },
  "message": "success",
  "code": 200
}
```

**Example Response — poll (completed)**:

```json
{
  "data": {
    "id": "pred_example_01",
    "model": "doubao-seedream-5-0-260128",
    "outputs": [
      "https://oss-us.gptproto.com/example/output.png"
    ],
    "urls": {
      "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result"
    },
    "status": "completed",
    "error": null,
    "executionTime": 12345,
    "timings": {
      "inference": 12000
    },
    "has_nsfw_contents": [],
    "created_at": "2026-01-01T12:00:00Z"
  },
  "message": "success",
  "code": 200
}
```

### Status Values

- `created` — Task accepted. Use `data.id` as `result_id` for polling.
- `running` — Generation is in progress. Keep polling.
- `completed` — Finished successfully. Generated files are in `data.outputs`.
- `failed` — Generation failed. Read `data.error` for the reason.

## Usage Examples

### 1. Submit a request

```bash
curl --request POST "https://gptproto.com/api/v3/doubao/doubao-seedream-5-0-260128/text-to-image" \
  --header "Authorization: Bearer $GPTPROTO_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
    "size": "2048x2048",
    "enable_base64_output": false,
    "enable_sync_mode": false
  }'
```

```python
import os
import requests

url = "https://gptproto.com/api/v3/doubao/doubao-seedream-5-0-260128/text-to-image"
headers = {
  "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}",
  "Content-Type": "application/json"
}
payload = {
  "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle",
  "size": "2048x2048",
  "enable_base64_output": False,
  "enable_sync_mode": False
}

response = requests.request("POST", url, headers=headers, json=payload)
print(response.json())
```

```typescript
const response = await fetch("https://gptproto.com/api/v3/doubao/doubao-seedream-5-0-260128/text-to-image", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    prompt: "A tiny origami fox sailing a teacup across a moonlit puddle",
    size: "2048x2048",
    enable_base64_output: false,
    enable_sync_mode: false,
  }),
});

const data = await response.json();
console.log(data);
```

### 2. Poll until the task finishes

Replace `YOUR_RESULT_ID` with `data.id` from the submit response (or call `data.urls.get` directly), and keep polling every 1–3 seconds while `status` is `created` or `running`.

```bash
result_id="YOUR_RESULT_ID"

curl --request GET "https://gptproto.com/api/v3/predictions/$result_id/result" \
  --header "Authorization: Bearer $GPTPROTO_API_KEY"
```

```python
import os
import requests

result_id = "YOUR_RESULT_ID"
url = f"https://gptproto.com/api/v3/predictions/{result_id}/result"
headers = {
  "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}"
}
response = requests.request("GET", url, headers=headers)
print(response.json())
```

```typescript
const result_id = "YOUR_RESULT_ID";
const response = await fetch(`https://gptproto.com/api/v3/predictions/${result_id}/result`, {
  method: "GET",
  headers: {
    "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`,
  },
});

const data = await response.json();
console.log(data);
```

## Example Prompts

- Young woman with auburn hair tied in a loose bun and emerald green silk blouse, sitting cross-legged on a velvet armchair while reading a weathered hardcover book with yellowed pages, tucked into a quiet corner of a rustic coffee shop surrounded by dark wood bookshelves and lush…
- A female artist with messy charcoal-smudged hair buns and paint-splattered linen overalls, applying thick impasto layers of cerulean and ochre paint to a large canvas with a palette knife, situated in a high-ceilinged industrial loft studio filled with stacked canvases and wooden…
- A veteran Japanese sushi chef wearing a crisp white chef's hat and a traditional dark blue indigo Happi coat, focusing intently while slicing a translucent piece of fresh ruby-red tuna with a long thin Damascus steel yanagiba knife on a minimalist Hinoki wood sushi counter, surro…

## HTTP Status Codes

- `400` — malformed body, a parameter or value this model does not accept, or input blocked by the provider's content moderation
- `401` — missing or invalid API key
- `403` — insufficient credits
- `413` — request body too large
- `429` — rate limited; retry with backoff
- `500` — An internal server error occurred
- `502` — An internal server error occurred
- `504` — Gateway timeout — upstream service did not respond in time; retry later

## Additional Resources

- [Model playground](https://gptproto.com/model/bytedance/doubao-seedream-5-0-260128)
- [API documentation](https://docs.gptproto.com/docs/allapi/Doubao/doubao-seedream-5-0-260128/gptproto-format/text-to-image)
- [All models](https://gptproto.com/model)
- [API keys](https://gptproto.com/dashboard/api-key)
- [Platform overview for LLMs](https://gptproto.com/llm-full.txt)
- Any other model: `https://gptproto.com/model/{vendor}/{model}/{scene}/llms.txt`