Hunyuan3D-V2-Mini is a Tencent image-to-3D generative model available on WaveSpeedAI. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.1per run·~10 / $1










Hunyuan3D V2 Mini 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 lightweight version delivers fast, affordable 3D generation without sacrificing quality.
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.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Source image to convert to 3D (upload or public URL). |
| Output | Price |
|---|---|
| Per 3D model | $0.10 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/hunyuan3d/v2-mini with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Hunyuan3d v2 Mini below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/hunyuan3d/v2-mini" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"image": "https://example.com/your-input.jpg"
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/hunyuan3d/v2-mini", {
"image": "https://example.com/your-input.jpg"
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/hunyuan3d/v2-mini",
{
"image": "https://example.com/your-input.jpg"
}
)
print(output["outputs"][0]) # → URL of the generated outputHunyuan3d v2 Mini is a WaveSpeedAI model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Hunyuan3D-V2-Mini is a Tencent image-to-3D generative model available on WaveSpeedAI. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/hunyuan3d-v2-mini.
Hunyuan3d v2 Mini starts at $0.10 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `image`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/hunyuan3d-v2-mini.
Average end-to-end generation time on WaveSpeedAI is around 510 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.