Hunyuan Part overview
Hunyuan Part by Tencent
It transforms complex OBJ and GLB models into clean, semantically meaningful components, enabling faster workflows in game development and animation.
Hunyuan Part specs
- Model ID
hunyuan-part- Developer
- Tencent
- Input
- Text, Image
- Output
- Image
- Endpoint
POST https://api.aimlapi.com/v1/images/generations
Hunyuan Part API Overview
Hunyuan Part is a specialized 3D AI model from the Tencent Hunyuan ecosystem designed to understand, analyze, and deconstruct complex 3D meshes into meaningful structural components. Instead of generating full objects, it focuses on what happens inside the geometry, identifying parts, boundaries, and functional regions that define how a model is built.
In modern 3D pipelines, raw meshes are often difficult to edit, rig, or reuse. Hunyuan Part solves this by transforming a single unified object into a structured collection of editable components, making it significantly easier to adapt assets for animation, game development, simulation, or digital manufacturing workflows.
Technical Overview
| Parameter | Description |
|---|---|
| Supported Input Formats | OBJ, GLB meshes |
| Output Structure | Independent 3D mesh components |
| Core Processing Method | Point-based sampling with semantic segmentation |
| Typical Mesh Density Handling | High-density geometry supported |
| Primary Function | Structural decomposition of 3D objects |
How Hunyuan Part Reframes 3D Understanding
Traditional segmentation tools rely heavily on geometric similarity, which often leads to inconsistent or visually inaccurate splits. Hunyuan Part takes a different approach by combining geometric reasoning with learned semantic structure, allowing it to understand what a part represents, not just how it looks.
In practice, this means the model can distinguish between components like handles, limbs, wheels, or mechanical joints even when their shapes are visually similar or partially obscured. This shift from surface-level clustering to semantic decomposition is what makes the system particularly effective in production environments.
The model processes standard 3D formats such as OBJ and GLB, converting them into structured representations that can be directly reused in downstream tools without manual cleanup. According to official documentation, it is optimized for dense mesh inputs and point-based sampling strategies that improve segmentation precision across complex geometry.
Focus on Production-Ready 3D Workflows
Hunyuan Part is designed specifically for real production environments where usability, accuracy, and structural consistency are more important than purely visual results. Its purpose is to support downstream pipelines such as animation, game development, and simulation by turning complex meshes into clean, structured components.
Structural Decomposition of 3D Objects
One of the core capabilities of the model is structural decomposition. It begins by analyzing the global shape of a 3D object and then progressively identifies boundaries between meaningful regions within the mesh.
Instead of treating the model as a single continuous surface, it systematically separates it into logically distinct parts. This process ensures that each component reflects a meaningful structural element rather than an arbitrary geometric split.
Semantic Awareness of Functional Components
Beyond geometry, Hunyuan Part incorporates semantic understanding of 3D structure. It does not treat objects as uniform surfaces but instead interprets functional relationships between different regions.
This allows it to consistently identify meaningful components such as limbs, mechanical joints, or structural attachments, even in complex or articulated models. As a result, segmentation remains stable and logically coherent across a wide range of 3D assets.
Use cases
- Professional Photo Retouching: Correction or enhancement of portraits, backgrounds, lighting, object removal/addition, while preserving original style.
- Advanced Photomontage: Combining multiple images/components into a single scene with consistent lighting and style.
- Visual Effects & Advertising: Scene adjustments, object insertion/removal, background replacement with natural blending.
- Product & E-commerce Imaging: Enhancing product photos, changing backgrounds, adjusting lighting, fine-tuning reflectance or material consistency.
Hunyuan Part API pricing
| Usage | Price | Unit |
|---|---|---|
| Image generation | $0.04 | per generation |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
Hunyuan Part vs other image models: prices
AI/ML API rates for 5 models, per generation.
| Model | Per generation |
|---|---|
 Hunyuan Part | $0.04 |
 Flux pro 1.1 | $0.04 |
| Flux.1 Kontext | $0.04 |
| Flux Kontext Pro | $0.04 |
 Nano Banana Edit | $0.04 |
How to use the Hunyuan Part API
View docs
Build with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/images/generations' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "hunyuan-part",
"mesh_url": "https://example.com/input.mp3"
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "hunyuan-part",
"mesh_url": "https://example.com/input.mp3"
}
response = requests.post("https://api.aimlapi.com/v1/images/generations", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/images/generations", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "hunyuan-part",
"mesh_url": "https://example.com/input.mp3"
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to Hunyuan Part
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Hunyuan Part FAQ
What inputs and outputs does Hunyuan Part support?
Hunyuan Part takes image, text as input and returns image.
How much does Hunyuan Part cost?
Hunyuan Part costs $0.04 per generation on AI/ML API, billed as you go with no subscription.
How is Hunyuan Part billed?
Hunyuan Part is billed per generation, a fixed charge per output rather than by prompt length.
Can Hunyuan Part take an existing image as input?
Yes, Hunyuan Part accepts image input as well as a text prompt.
Who created Hunyuan Part?
Hunyuan Part was built by Tencent.
How do I call Hunyuan Part on AI/ML API?
Send a request to https://api.aimlapi.com/v1/images/generations with hunyuan-part as the model id.
Is Hunyuan Part available through a single API key?
Yes. Hunyuan Part is served through AI/ML API, so the same key and endpoint format used for other models applies.
What is the Hunyuan Part model ID?
Use hunyuan-part as the model parameter. Requests go to https://api.aimlapi.com/v1/images/generations with your AI/ML API key.