# Trellis 2 API

> 将单张图像转换为带纹理的 GLB 3D 网格，可调节结构、形状、纹理和 UV 设置

根据一张图像（`image_url`）构建 3D 资产并返回 GLB 文件。`resolution` 为 512、1024 或 1536，`texture_size` 为 1024、2048 或 4096。三个阶段（结构、形状、纹理）分别具有独立的引导和采样步数控制。`decimation_target` 设置网格顶点数（5,000 到 2,000,000），并提供重新网格化和 UV 展开选项。

- 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/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 |  |  | 用于可复现随机生成的种子。 |
| `resolution` |  | enum (integer) | no | `1024` | `512`, `1024`, `1536` | 输出分辨率；提高分辨率会增加细节，但耗时更长。 |
| `ss_guidance_strength` |  | number | no | `7.5` | 0 – 10 | 初始 3D 结构保真度控制：提高该值可更贴近输入图像，但可能增加噪声。 |
| `ss_guidance_rescale` |  | number | no | `0.7` | 0 – 1 | 第 1 阶段的引导伪影控制：较低设置会产生更强的引导效果，较高设置会带来更稳定的输出。 |
| `ss_guidance_interval_start` |  | number | no | `0.6` | 0 – 1 | 阶段 1（稀疏结构）无分类器指导窗口的起始边界，以降噪比例表示。值越低，指导开始越早；只有 interval_start 到 interval_end 的区间使用指导，其他部分不使用指导。 |
| `ss_guidance_interval_end` |  | number | no | `1` | 0 – 1 | 阶段 1（稀疏结构）的指导截止点：选择不小于 ss_guidance_interval_start 的值。该值表示无分类器指导停止时达到的降噪比例。 |
| `ss_sampling_steps` |  | integer | no | `12` | 1 – 50 | 初始结构去噪步数：增加步数可能提升质量，但会降低处理速度。 |
| `ss_rescale_t` |  | number | no | `5` | 1 – 6 | 通过结构生成噪声调度设置过渡锐度：提高该值会使过渡更锐利。 |
| `shape_slat_guidance_strength` |  | number | no | `7.5` | 0 – 10 | 详细几何保真度控制：提高对输入图像的遵循程度会增加细节，但也可能增加噪声。 |
| `shape_slat_guidance_rescale` |  | number | no | `0.5` | 0 – 1 | 当几何结构出现噪声时提高此设置：它会减少形状阶段强引导造成的伪影。 |
| `shape_slat_guidance_interval_start` |  | number | no | `0.6` | 0 – 1 | 阶段 2 形状细化的无分类器指导启用点。该值表示降噪进度的比例，并设置 interval_start；指导仅在由 interval_start 和 interval_end 界定的窗口内运行。 |
| `shape_slat_guidance_interval_end` |  | number | no | `1` | 0 – 1 | 阶段 2（形状细化）的指导截止点：选择不小于 shape_slat_guidance_interval_start 的值。该值表示无分类器指导停止时达到的降噪比例。 |
| `shape_slat_sampling_steps` |  | integer | no | `12` | 1 – 50 | 形状细化去噪步数：增加步数可能使几何结构更平滑，但会牺牲速度。 |
| `shape_slat_rescale_t` |  | number | no | `3` | 1 – 6 | 通过形状细化噪声调度设置几何细节锐度；提高该值会产生更锐利的细节。 |
| `tex_slat_guidance_strength` |  | number | no | `1` | 0 – 10 | 纹理颜色保真度控制：较高设置会更贴近输入图像的颜色并提高鲜艳度，但可能导致过度饱和。 |
| `tex_slat_guidance_rescale` |  | number | no | `0` | 0 – 1 | 提高此设置以处理噪声纹理或色带：它会减少纹理阶段强引导造成的伪影。 |
| `tex_slat_guidance_interval_start` |  | number | no | `0.6` | 0 – 1 | 阶段 3 纹理生成的无分类器指导启用点。该值表示降噪进度的比例，并设置 interval_start；指导仅在由 interval_start 和 interval_end 界定的窗口内运行。 |
| `tex_slat_guidance_interval_end` |  | number | no | `0.9` | 0 – 1 | 阶段 3（纹理）的指导截止点：选择不小于 tex_slat_guidance_interval_start 的值。该值表示无分类器指导停止时达到的降噪比例。 |
| `tex_slat_sampling_steps` |  | integer | no | `12` | 1 – 50 | 用于生成纹理的去噪步数。增加步数会延长处理时间，但可能产生更干净的纹理。 |
| `tex_slat_rescale_t` |  | number | no | `3` | 1 – 6 | 通过纹理生成噪声调度设置纹理细节锐度；提高该值会产生更锐利的细节。 |
| `decimation_target` |  | integer | no | `500000` | 5,000 – 2,000,000 | 网格顶点数目标值，通用场景推荐 500k，网页或移动设备推荐 20k–50k。降低目标值会以网格细节换取更小的文件。 |
| `texture_size` |  | enum (integer) | no | `2048` | `1024`, `2048`, `4096` | 用于烘焙的网格纹理分辨率。提高分辨率可获得更精细的表面细节，但会生成更大的文件。 |
| `remesh` |  | boolean | no | `true` |  | 重建拓扑以创建更整洁的网格三角形，通常会提高后续动画或 3D 打印等用途的适用性，但处理速度会降低。 |
| `remesh_band` |  | number | no | `1` | 0 – 4 | 重新网格化移动容差：提高此值时，额外平滑可能会牺牲精细细节。此设置限制相对于原始表面的顶点位移。 |
| `remesh_project` |  | number | no | `0` | 0 – 1 | 将重新网格化后的顶点投影回原始表面的强度：1 表示完全投影以保留细节，0 表示关闭投影以获得更平滑的结果。 |
| `uv_unwrap_angle_threshold_deg` |  | number | no | `90` | 0 – 180 | UV 图表角度限制，单位为度，用于限制一个图表内相邻面法线之间的差异。提高限制值倾向于生成更少、更大的图表，但可能产生拉伸；降低限制值倾向于生成更多图表并减少失真。 |
| `uv_unwrap_refine_iterations` |  | integer | no | `0` | 0 – 10 | 用于计算 UV 图表的局部细化遍数。 |
| `uv_unwrap_global_iterations` |  | integer | no | `1` | 1 – 10 | 增加用于计算图表的全局聚类遍数，可改善 UV 图表平衡。 |
| `uv_unwrap_smooth_strength` |  | number | no | `1` | 0 – 10 | 调整 UV 图表边缘的平滑程度；较高设置可减少可见接缝，但存在 UV 失真的风险。 |
| `image_url` | `image` | string (image URL) | yes |  |  | 指向用于 3D 转换的源图像的 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