# Trellis 2 API

> 將單張圖片轉換為具有紋理的 GLB 3D 網格，可調整結構、形狀、紋理與 UV 設定

從單張圖片（`image_url`）建立 3D 素材並回傳 GLB 檔案。`resolution` 可為 512、1024 或 1536，`texture_size` 可為 1024、2048 或 4096。三個階段（結構、形狀、紋理）各自具有引導與採樣步數控制。`decimation_target` 設定網格頂點數（5,000 到 2,000,000），並提供重新網格化與 UV 展開選項。

- Model id: `trellis-2`
- Made by: Microsoft
- Category: Image to 3D
- Output: 3d
- Price: from $0.25 / request (cheapest run $0.25 (250 API credits))
- Run: `POST https://api.doitong.com/v1/run/trellis-2`
- Quote: `POST https://api.doitong.com/v1/quote/trellis-2`
- Docs page: https://doitong.com/zh-TW/developers/models/trellis-2

## Pricing

Price: **from $0.25 / 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` = 1024: $0.30 (300 API credits) / request
- When `resolution` = 1536: $0.35 (350 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/trellis-2` 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 |
|---|---|---|---|---|---|---|
| `seed` |  | integer \| null | no |  |  | 用於可重現隨機生成的種子。 |
| `resolution` |  | enum (integer) | no | `1024` | `512`, `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_guidance_interval_start` |  | number | no | `0.6` | 0 – 1 | 第 1 階段（稀疏結構）無分類器指引視窗的起始邊界，以降噪比例表示。較低設定會較早開始指引；只有 interval_start 至 interval_end 的區間使用指引，其餘部分不使用指引。 |
| `ss_guidance_interval_end` |  | number | no | `1` | 0 – 1 | 第 1 階段（稀疏結構）的指引截止點：請選擇至少等於 ss_guidance_interval_start 的值。此值表示無分類器指引停止時已達到的降噪比例。 |
| `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_guidance_interval_start` |  | number | no | `0.6` | 0 – 1 | 第 2 階段形狀細化的無分類器指引啟用點。以降噪進度的比例表示，會設定 interval_start；指引僅在由 interval_start 和 interval_end 界定的視窗內運作。 |
| `shape_slat_guidance_interval_end` |  | number | no | `1` | 0 – 1 | 第 2 階段（形狀細化）的指引截止點：請選擇至少等於 shape_slat_guidance_interval_start 的值。此值表示無分類器指引停止時已達到的降噪比例。 |
| `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_guidance_interval_start` |  | number | no | `0.6` | 0 – 1 | 第 3 階段紋理生成的無分類器指引啟用點。以降噪進度的比例表示，會設定 interval_start；指引僅在由 interval_start 和 interval_end 界定的視窗內運作。 |
| `tex_slat_guidance_interval_end` |  | number | no | `0.9` | 0 – 1 | 第 3 階段（紋理）的指引截止點：請選擇至少等於 tex_slat_guidance_interval_start 的值。此值表示無分類器指引停止時已達到的降噪比例。 |
| `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。 |
| `decimation_target` |  | integer | no | `500000` | 5,000 – 2,000,000 | 網格頂點數目目標，一般用途建議使用 500k，網頁／行動裝置建議使用 20k–50k。降低目標會以網格細節換取較小的檔案。 |
| `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` |  | 重建拓撲以建立更乾淨的網格三角形，通常能提升後續動畫或 3D 列印等用途的適用性，但處理速度會變慢。 |
| `remesh_band` |  | number | no | `1` | 0 – 4 | 重新網格化的移動容許量：提高此值時，額外平滑可能犧牲精細細節。此設定會限制頂點相對於原始表面的位移。 |
| `remesh_project` |  | number | no | `0` | 0 – 1 | 將重新網格化後的頂點投影回原始表面的強度：1 會透過完整投影保留細節，0 則關閉投影以產生更平滑的結果。 |
| `uv_unwrap_angle_threshold_deg` |  | number | no | `90` | 0 – 180 | UV 圖表角度限制，單位為度，用於限制單一圖表內相鄰面法線的差異程度。提高限制值會偏向較少且較大的圖表，但可能造成拉伸；降低限制值則偏向較多圖表與較少失真。 |
| `uv_unwrap_refine_iterations` |  | integer | no | `0` | 0 – 10 | 用於計算 UV 圖表的區域細化 pass 數。 |
| `uv_unwrap_global_iterations` |  | integer | no | `1` | 1 – 10 | 增加用於計算圖表的全域分群 pass 數，可改善 UV 圖表平衡。 |
| `uv_unwrap_smooth_strength` |  | number | no | `1` | 0 – 10 | 調整 UV 圖表邊緣的平滑程度；較高設定可減少可見接縫，但有 UV 失真的風險。 |
| `image_url` | `image` | string (image URL) | yes |  |  | 指向用於 3D 轉換之來源圖像的 URL。 |

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/trellis-2?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/trellis-2?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/trellis-2", 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": "trellis-2",
      "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": "trellis-2",
  "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
    }
  },
  "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。 |

## Related models

- [Trellis 2 · Retexture](https://doitong.com/developers/models/trellis-2/retexture.md) (`trellis-2/retexture`): from $0.20 / request
- [Trellis](https://doitong.com/developers/models/trellis.md) (`trellis`): $0.02 / request
- [Trellis · Multi](https://doitong.com/developers/models/trellis/multi.md) (`trellis/multi`): $0.02 / request
- [TRELLIS.2 LoRA Inference](https://doitong.com/developers/models/trellis-2-lora.md) (`trellis-2-lora`): 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

## Links

- HTML page: https://doitong.com/developers/models/trellis-2
- 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=trellis-2
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/trellis-2