ByteDance Seed3D 2.0 — generates a textured, PBR-shaded 3D model (glb/obj/usd/usdz) from a single input image. Returns a downloadable .zip archive containing the 3D file.
Your request will cost $0.353 per run. For $10 you can run this model approximately 28 times.
import requests
import time
# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "bytedance/seed3d-v2.0/image-to-3d", # Required. model name
"image": "example_value", # Required. Source image (URL or base64 data URI)
"subdivision_level": "medium", # Subdivision level for the generated 3D mesh. options: high | medium | low
"file_format": "glb", # Output 3D file format. options: glb | obj | usd | usdz
"enable_base64_output": False, # If enabled, the output will be encoded into a BASE64 string instead of a URL
}
generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]
# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
def check_status():
while True:
response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
result = response.json()
if result["data"]["status"] == "completed":
print("Generated image:", result["data"]["outputs"][0])
return result["data"]["outputs"][0]
elif result["data"]["status"] == "failed":
raise Exception(result["data"]["error"] or "Generation failed")
else:
# Still processing, wait 2 seconds
time.sleep(2)
image_url = check_status()Install the required package for your language.
pip install requestsAll API requests require authentication via an API key. You can get your API key from the Atlas Cloud dashboard.
export ATLASCLOUD_API_KEY="your-api-key-here"import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}Never expose your API key in client-side code or public repositories. Use environment variables or a backend proxy instead.
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "your-model",
"prompt": "A beautiful landscape"
}
response = requests.post(url, headers=headers, json=data)
print(response.json())Submit an asynchronous generation request. The API returns a prediction ID that you can use to check the status and retrieve the result.
/api/v1/model/generateImageimport requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "bytedance/seed3d-v2.0/image-to-3d",
"prompt": "A beautiful landscape with mountains and lake"
}
response = requests.post(url, headers=headers, json=data)
result = response.json()
print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}"){
"code": 200,
"data": {
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}
}Poll the prediction endpoint to check the current status of your request.
/api/v1/model/prediction/{prediction_id}import requests
import time
prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
while True:
response = requests.get(url, headers=headers)
result = response.json()
status = result["data"]["status"]
print(f"Status: {status}")
if status in ["completed", "succeeded"]:
output_url = result["data"]["outputs"][0]
print(f"Output URL: {output_url}")
break
elif status == "failed":
print(f"Error: {result['data'].get('error', 'Unknown')}")
break
time.sleep(3)processingThe request is still being processed.completedGeneration is complete. Outputs are available.succeededGeneration succeeded. Outputs are available.failedGeneration failed. Check the error field.{
"data": {
"id": "pred_abc123",
"status": "completed",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.png"
],
"metrics": {
"predict_time": 8.3
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}
}Upload files to Atlas Cloud storage and get a URL you can use in your API requests. Use multipart/form-data to upload.
/api/v1/model/uploadMediaimport requests
url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
with open("image.png", "rb") as f:
files = {"file": ("image.png", f, "image/png")}
response = requests.post(url, headers=headers, files=files)
result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}"){
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}The following parameters are accepted in the request body.
{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": "example_image",
"subdivision_level": "medium",
"file_format": "glb",
"enable_base64_output": false
}The API returns a prediction response with the generated output URLs.
{
"id": "pred_abc123",
"status": "completed",
"model": "model-name",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.png"
],
"metrics": {
"predict_time": 8.3
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}Atlas Cloud Skills integrates 400+ AI models directly into your AI coding assistant. One command to install, then use natural language to generate images, videos, and chat with LLMs.
npx skills add AtlasCloudAI/atlas-cloud-skillsGet your API key from the Atlas Cloud dashboard and set it as an environment variable.
export ATLASCLOUD_API_KEY="your-api-key-here"Once installed, you can use natural language in your AI assistant to access all Atlas Cloud models.
Atlas Cloud MCP Server connects your IDE with 400+ AI models via the Model Context Protocol. Works with any MCP-compatible client.
npx -y atlascloud-mcpAdd the following configuration to your IDE's MCP settings file.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}{
"openapi": "3.0.0",
"info": {
"title": "AtlasCloud API",
"version": "1.0.0",
"description": "The AtlasCloud API."
},
"servers": [
{
"url": "https://api.atlascloud.ai"
}
],
"paths": {
"/api/v1/model/generateImage": {
"post": {
"requestBody": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/Input"
}
}
},
"required": true
},
"responses": {
"200": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PredictionResponse"
}
}
},
"description": "The request status."
}
},
"x-api-name": "model_run"
}
},
"/api/v1/model/result/{request_id}": {
"get": {
"parameters": [
{
"in": "path",
"name": "request_id",
"required": true,
"schema": {
"description": "Request ID",
"type": "string"
}
}
],
"responses": {
"200": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PredictionResponse"
}
}
},
"description": "Result of the request."
}
},
"x-api-name": "model_result"
}
}
},
"components": {
"schemas": {
"Input": {
"type": "object",
"properties": {
"model": {
"type": "string",
"description": "model name",
"default": "bytedance/seed3d-v2.0/image-to-3d"
},
"image": {
"type": "string",
"description": "Source image (URL or base64 data URI). Constraints: total pixels < 4096x4096, size <= 10 MB, aspect ratio in (0.4, 2.5), formats: jpg, jpeg, png, webp, bmp."
},
"subdivision_level": {
"type": "string",
"description": "Subdivision level for the generated 3D mesh. high=1,000,000 / medium=500,000 / low=100,000 polygon faces.",
"enum": [
"high",
"medium",
"low"
],
"default": "medium"
},
"file_format": {
"type": "string",
"description": "Output 3D file format. The result is delivered as a .zip archive containing a single file in the chosen format.",
"enum": [
"glb",
"obj",
"usd",
"usdz"
],
"default": "glb"
},
"enable_base64_output": {
"type": "boolean",
"description": "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,
"disabled": true
}
},
"required": [
"model",
"image"
],
"x-order-properties": [
"model",
"image",
"subdivision_level",
"file_format",
"enable_base64_output"
]
},
"PredictionResponse": {
"type": "object",
"properties": {
"created_at": {
"description": "ISO timestamp of when the request was created (e.g., \"2023-04-01T12:34:56.789Z\").",
"format": "date-time",
"type": "string"
},
"id": {
"description": "Unique identifier for the prediction, the ID of the prediction to get.",
"type": "string"
},
"model": {
"description": "Model ID used for the prediction.",
"type": "string"
},
"outputs": {
"description": "Array containing one URL pointing to the generated 3D file .zip archive (empty when status is not completed). The URL is valid for 24 hours.",
"items": {
"type": "string"
},
"type": "array"
},
"status": {
"description": "Status of the task: created, processing, completed, or failed.",
"type": "string"
},
"urls": {
"description": "Object containing related API endpoints.",
"type": "object"
}
}
}
}
}
}# bytedance/seed3d-v2.0/image-to-3d
> ByteDance Seed3D 2.0 — generates a textured, PBR-shaded 3D model (glb/obj/usd/usdz) from a single input image. Returns a downloadable .zip archive containing the 3D file.
## Overview
- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `bytedance/seed3d-v2.0/image-to-3d`
## API Information
This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.
### Input Schema
The API accepts the following input parameters:
- **`model`** (`string`, _required_):
model name
- Default: `"bytedance/seed3d-v2.0/image-to-3d"`
- **`image`** (`string`, _required_):
Source image (URL or base64 data URI). Constraints: total pixels < 4096x4096, size <= 10 MB, aspect ratio in (0.4, 2.5), formats: jpg, jpeg, png, webp, bmp.
- **`subdivision_level`** (`string`, _optional_):
Subdivision level for the generated 3D mesh. high=1,000,000 / medium=500,000 / low=100,000 polygon faces.
- Default: `"medium"`
- Options: "high", "medium", "low"
- **`file_format`** (`string`, _optional_):
Output 3D file format. The result is delivered as a .zip archive containing a single file in the chosen format.
- Default: `"glb"`
- Options: "glb", "obj", "usd", "usdz"
- **`enable_base64_output`** (`boolean`, _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`
**Required Parameters Example**:
```json
{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": ""
}
```
**Full Example**:
```json
{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": "",
"subdivision_level": "medium",
"file_format": "glb",
"enable_base64_output": false
}
```
### Output Schema
The API returns the following output format:
- **`created_at`** (`string`, _optional_):
ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").
- **`id`** (`string`, _optional_):
Unique identifier for the prediction, the ID of the prediction to get.
- **`model`** (`string`, _optional_):
Model ID used for the prediction.
- **`outputs`** (`array[string]`, _optional_):
Array containing one URL pointing to the generated 3D file .zip archive (empty when status is not completed). The URL is valid for 24 hours.
- **`status`** (`string`, _optional_):
Status of the task: created, processing, completed, or failed.
- **`urls`** (`object`, _optional_):
Object containing related API endpoints.
**Example Response**:
```json
{
"created_at": "",
"id": "",
"model": "",
"outputs": [
""
],
"status": "",
"urls": {}
}
```
## Usage Examples
### cURL
```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
-H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": "",
"subdivision_level": "medium",
"file_format": "glb",
"enable_base64_output": false
}'
# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}
# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
-H "Authorization: Bearer $ATLASCLOUD_API_KEY"
# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```
## Additional Resources
### Documentation
- [Model Playground](https://www.atlascloud.ai/models/bytedance/seed3d-v2.0/image-to-3d)
No 3D output