Trellis 2 | Image to 3D

fal-ai/trellis-2

Generate 3D models from your images using Trellis 2. A native 3D generative model enabling versatile and high-quality 3D asset creation.

Inference

Commercial use

Schema

LLMs

Playground API

About

Generate

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Please check the migration guide for more information.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/trellis-2", {
  input: {
    image_url: "https://v3b.fal.media/files/b/0a86b60d/xkpao5B0uxmH0tmJm0HVL_2fe35ce1-fe44-475b-b582-6846a149537c.png"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.

3. Queue#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/trellis-2", {
  input: {
    image_url: "https://v3b.fal.media/files/b/0a86b60d/xkpao5B0uxmH0tmJm0HVL_2fe35ce1-fe44-475b-b582-6846a149537c.png"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/trellis-2", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/trellis-2", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

seed integer

Random seed for reproducibility

resolution ResolutionEnum

Output resolution; higher is slower but more detailed Default value: "1024"

Possible enum values: 512, 1024, 1536

ss_guidance_strength float

Default value: 7.5

ss_guidance_rescale float

Default value: 0.7

ss_sampling_steps integer

Default value: 12

ss_rescale_t float

Default value: 5

shape_slat_guidance_strength float

Default value: 7.5

shape_slat_guidance_rescale float

Default value: 0.5

shape_slat_sampling_steps integer

Default value: 12

shape_slat_rescale_t float

Default value: 3

tex_slat_guidance_strength float

Default value: 1

tex_slat_guidance_rescale float

tex_slat_sampling_steps integer

Default value: 12

tex_slat_rescale_t float

Default value: 3

decimation_target integer

Target vertex count for mesh simplification during export Default value: 500000

texture_size TextureSizeEnum

Texture resolution Default value: "2048"

Possible enum values: 1024, 2048, 4096

remesh boolean

Run remeshing (slower; often improves topology) Default value: true

remesh_band float

Default value: 1

remesh_project float

image_url string* required

URL of the input image to convert to 3D

{
  "resolution": 1024,
  "ss_guidance_strength": 7.5,
  "ss_guidance_rescale": 0.7,
  "ss_sampling_steps": 12,
  "ss_rescale_t": 5,
  "shape_slat_guidance_strength": 7.5,
  "shape_slat_guidance_rescale": 0.5,
  "shape_slat_sampling_steps": 12,
  "shape_slat_rescale_t": 3,
  "tex_slat_guidance_strength": 1,
  "tex_slat_sampling_steps": 12,
  "tex_slat_rescale_t": 3,
  "decimation_target": 500000,
  "texture_size": 2048,
  "remesh": true,
  "remesh_band": 1,
  "image_url": "https://v3b.fal.media/files/b/0a86b60d/xkpao5B0uxmH0tmJm0HVL_2fe35ce1-fe44-475b-b582-6846a149537c.png"
}

Output#

model_glb File* required

Generated 3D GLB file

{
  "model_glb": {
    "url": "https://v3b.fal.media/files/b/0a86b61d/DNmTkiWHUQ8k-rG6aussB_trellis2_68d6300f70f34d23b69a912b5fe60487.glb"
  }
}

Other types#

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

file_data string

File data

MultiImageInputModel#

seed integer

Random seed for reproducibility

resolution ResolutionEnum

Output resolution; higher is slower but more detailed Default value: "1024"

Possible enum values: 512, 1024, 1536

ss_guidance_strength float

Default value: 7.5

ss_guidance_rescale float

Default value: 0.7

ss_sampling_steps integer

Default value: 12

ss_rescale_t float

Default value: 5

shape_slat_guidance_strength float

Default value: 7.5

shape_slat_guidance_rescale float

Default value: 0.5

shape_slat_sampling_steps integer

Default value: 12

shape_slat_rescale_t float

Default value: 3

tex_slat_guidance_strength float

Default value: 1

tex_slat_guidance_rescale float

tex_slat_sampling_steps integer

Default value: 12

tex_slat_rescale_t float

Default value: 3

decimation_target integer

Target vertex count for mesh simplification during export Default value: 500000

texture_size TextureSizeEnum

Texture resolution Default value: "2048"

Possible enum values: 1024, 2048, 4096

remesh boolean

Run remeshing (slower; often improves topology) Default value: true

remesh_band float

Default value: 1

remesh_project float

image_urls list<string>* required

Multiple views of the same object. Conditioning is averaged across views.

Trellis 2 Image to 3D

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

File#

MultiImageInputModel#