# Pixal3d API

> 將單張圖片轉換為具材質的 GLB 3D 模型，並可詳細控制每個生成階段

提供一張圖像並回傳 GLB 模型及所使用的種子。結構、形狀和貼圖階段各自擁有引導、重新縮放、步驟數和雜訊排程設定。輸出 `resolution` 為 1024 或 1536，`texture_size` 為 1024、2048 或 4096，`decimation_target` 將頂點數設為 5000 到 1586021。`remesh` 會重建拓撲。

- Model id: `pixal3d`
- Made by: Open model
- Category: Image to 3D
- Output: 3d
- Price: from $0.30 / request (cheapest run $0.30 (300 API credits))
- Run: `POST https://api.doitong.com/v1/run/pixal3d`
- Quote: `POST https://api.doitong.com/v1/quote/pixal3d`
- Docs page: https://doitong.com/zh-TW/developers/models/pixal3d

## Pricing

Price: **from $0.30 / request** (the lowest tier; the quote prices your exact input). Billed once per request.

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `resolution` = 1536: $0.42 (420 API credits) / request

The full example input below costs $0.30 = 300 API credits (1 request × 300 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/pixal3d` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | 指向用於 3D 轉換之來源圖像的 URL。 |
| `seed` |  | integer \| null | no |  |  | 用於可重現隨機生成的種子。 |
| `resolution` |  | enum (integer) | no | `1024` | `1024`, `1536` | 輸出解析度；提高解析度會增加細節，但需要更長時間。 |
| `ss_guidance_strength` |  | number | no | `7.5` | 0 – 10 | 初始 3D 結構保真度控制：提高此值可更貼近輸入圖像，但可能增加雜訊。 |
| `ss_guidance_rescale` |  | number | no | `0.7` | 0 – 1 | 第 1 階段的引導瑕疵控制；低設定值會產生較強的引導效果，高設定值則可得到更穩定的輸出。 |
| `ss_sampling_steps` |  | integer | no | `12` | 1 – 50 | 初始結構去噪次數：增加步驟可能提升品質，但會降低處理速度。 |
| `ss_rescale_t` |  | number | no | `5` | 1 – 6 | 透過結構生成的雜訊排程設定轉場銳利度；提高此值會使轉場更銳利。 |
| `shape_slat_guidance_strength` |  | number | no | `7.5` | 0 – 10 | 詳細幾何保真度控制：提高對輸入圖像的遵循程度可增加細節，但可能增加雜訊。 |
| `shape_slat_guidance_rescale` |  | number | no | `0.5` | 0 – 1 | 幾何形狀看起來有雜訊時提高此設定：可減少形狀階段強引導造成的瑕疵。 |
| `shape_slat_sampling_steps` |  | integer | no | `12` | 1 – 50 | 形狀精修去噪次數：增加步驟可能產生更平滑的幾何形狀，但會犧牲速度。 |
| `shape_slat_rescale_t` |  | number | no | `3` | 1 – 6 | 透過形狀精修的雜訊排程設定幾何細節銳利度；提高此值會產生更銳利的細節。 |
| `tex_slat_guidance_strength` |  | number | no | `1` | 0 – 10 | 紋理色彩保真度控制：較高設定值會更貼近輸入圖像的色彩並提高鮮明度，但可能導致過度飽和。 |
| `tex_slat_guidance_rescale` |  | number | no | `0` | 0 – 1 | 紋理有雜訊或色帶時提高此設定：可減少紋理階段強引導造成的瑕疵。 |
| `tex_slat_sampling_steps` |  | integer | no | `12` | 1 – 50 | 用於生成紋理的去噪步驟數。增加步驟數需要更長時間，但可能產生更乾淨的紋理。 |
| `tex_slat_rescale_t` |  | number | no | `3` | 1 – 6 | 透過紋理生成的雜訊排程設定紋理細節銳利度；提高此值會產生更銳利的細節。 |
| `mesh_scale` |  | number | no | `1` | 0.1 – 4 | 縮放推斷出的網格，以影響模型使用的相機距離估算值。 |
| `max_num_tokens` |  | integer | no | `49152` | 4,096 – 131,072 | 串接形狀取樣器的 HR Token 上限；較高設定可取得更精細的幾何形狀，較低設定則可節省記憶體與處理時間。 |
| `decimation_target` |  | integer | no | `200000` | 5,000 – 1,586,021 | 網格複雜度目標，以最終結果的頂點數量表示。降低此目標可減少檔案大小，但也會犧牲細節。 |
| `texture_size` |  | enum (integer) | no | `2048` | `1024`, `2048`, `4096` | 用於烘焙的網格紋理解析度。提高解析度可取得更精細的表面細節，但會產生更大的檔案。 |
| `remesh` |  | boolean | no | `true` |  | 重建網格拓撲；透過建立更乾淨的三角形，通常有利於後續使用，但會延長處理時間。 |
| `enable_safety_checker` |  | boolean | no | `true` |  | 在呼叫端獲得授權的情況下，將此值設為 false 可放寬審核。 |

File parameters (`image`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/pixal3d?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/pixal3d?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/pixal3d", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.com/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "pixal3d",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "pixal3d",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 300,
    "usd": "0.30",
    "charged": 300,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "model_glb": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "seed": 42
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `model_glb` | object {url, content_type, file_name, file_size} | 以 GLB 格式生成的 3D 模型。 |
| `seed` | integer | 實際使用的種子值。 |

## Related models

- [ReconViaGen 0.5](https://doitong.com/developers/models/reconviagen-0.5.md) (`reconviagen-0.5`): from $0.25 / request
- [Hi3D Image to 3D](https://doitong.com/developers/models/hitem3d/hi3d/image-to-3d.md) (`hitem3d/hi3d/image-to-3d`): $0.50 / run
- [Hi3D Image to 3D · v3.0](https://doitong.com/developers/models/hitem3d/hi3d/v3.0/image-to-3d.md) (`hitem3d/hi3d/v3.0/image-to-3d`): from $1.80 / run
- [Hi3D Multiview to 3D · Multi View to 3D](https://doitong.com/developers/models/hitem3d/hi3d/multi-view-to-3d.md) (`hitem3d/hi3d/multi-view-to-3d`): $0.50 / run
- [Hi3D Multiview to 3D · v3.0 · Multi View to 3D](https://doitong.com/developers/models/hitem3d/hi3d/v3.0/multi-view-to-3d.md) (`hitem3d/hi3d/v3.0/multi-view-to-3d`): from $1.80 / run
- [Hunyuan 3D Pro Image to 3D](https://doitong.com/developers/models/hunyuan-3d/v3.1/pro/image-to-3d.md) (`hunyuan-3d/v3.1/pro/image-to-3d`): $0.375 / run
- [Hunyuan 3D Rapid Image to 3D](https://doitong.com/developers/models/hunyuan-3d/v3.1/rapid/image-to-3d.md) (`hunyuan-3d/v3.1/rapid/image-to-3d`): from $0.225 / request
- [Hunyuan World · Image to World](https://doitong.com/developers/models/hunyuan_world/image-to-world.md) (`hunyuan_world/image-to-world`): $0.30 / request

## Links

- HTML page: https://doitong.com/developers/models/pixal3d
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=pixal3d
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/pixal3d