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Hunyuan3d V2 Base

Hunyuan3d V2 Base

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Hunyuan3D-V2-Base is a state-of-the-art Image-to-3D model by Tencent that turns images into 3D assets for visualization and content. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Hunyuan3D V2 Base — Image-to-3D

Hunyuan3D V2 Base is part of Tencent’s open-source Hunyuan3D-2 series — a state-of-the-art 3D generation system that transforms 2D images into high-fidelity 3D models with detailed textures. This full-featured version delivers superior quality and detail for professional 3D generation needs.


Why It Stands Out

  • Single image input: Generate complete 3D models from just one 2D image.
  • High-fidelity output: Produces detailed 3D models with accurate geometry and high-resolution (4K) textures.
  • Superior quality: Full model capabilities for maximum detail and precision.
  • Decoupled architecture: Separates geometry generation and texture synthesis for improved quality.
  • Simple workflow: Just upload an image — no 3D expertise required.

Technical Highlights

The Hunyuan3D-2 system adopts a separated process of geometry generation + texture synthesis:

  • Geometry Generation (Hunyuan3D-DiT): Based on a flow diffusion model that generates untextured 3D geometric models, with 2.6B parameters, capable of precisely extracting geometric information from input images.

  • Texture Synthesis (Hunyuan3D-Paint): Adds high-resolution (4K) textures to geometric models, with 1.3B parameters, supporting multi-view diffusion generation technology to ensure realistic textures and consistent lighting.

By decoupling shape and texture generation, the system effectively reduces complexity and improves generation quality.


Performance and Efficiency

  • High-Quality Output: Full model delivers maximum detail and texture resolution.
  • Multi-modal Support: Compatible with various input methods and integrations including Blender plugins and Gradio applications.
  • Open Source Ecosystem: Part of Tencent’s open-source 3D generation initiative.

Parameters

ParameterRequiredDescription
imageYesSource image to convert to 3D (upload or public URL).

How to Use

  1. Upload your image — drag and drop a file or paste a public URL.
  2. Click Run and wait for the 3D model to generate.
  3. Preview and download the result.

Best Use Cases

  • Game Development — Generate production-ready 3D assets from concept art.
  • E-commerce — Create detailed 3D product models for interactive displays.
  • 3D Printing — Convert 2D designs into high-detail printable 3D models.
  • AR/VR Content — Generate quality 3D objects for immersive experiences.
  • Film & Animation — Create 3D assets from character designs and storyboards.
  • Product Visualization — Transform product photos into interactive 3D models.

Pricing

OutputPrice
Per 3D model$0.16

Model Comparison

ModelPriceBest For
Hunyuan3D V2 Mini$0.10Quick prototypes, icons, simple objects
Hunyuan3D V2 Base$0.16Production assets, detailed models

Pro Tips for Best Quality

  • Use images with clear subjects against simple or transparent backgrounds.
  • Front-facing or 3/4 angle views typically produce the best results.
  • Ensure the subject is well-lit and clearly visible in the image.
  • Higher resolution source images yield more detailed 3D models.
  • For complex objects, use images that clearly show the main features.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • Processing time varies based on image complexity and current queue load.
  • For faster, more affordable generation, consider using Hunyuan3D V2 Mini.
  • Please ensure your content complies with usage guidelines.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/hunyuan3d/v2-base" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
imagestringYes-URL of image to use while generating the 3D model.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction, the ID of the prediction to get
data.modelstringModel ID used for the prediction
data.outputsstringArray of URLs to the generated content (empty when status is not completed).
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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