Hunyuan3D V2 Multi-View is Tencent's image-to-3D generative model on WaveSpeedAI that builds 3D reconstructions from multi-view images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.01per run·~100 / $1






Hunyuan3D V2 Multi-View is an advanced multi-view 3D reconstruction model that creates detailed 3D models from multiple reference images. Provide front, back, and left views of your subject, and the model generates accurate 3D geometry with optional textures.
| Parameter | Required | Description |
|---|---|---|
| front_image_url | Yes | Front view image of the subject (upload or public URL). |
| back_image_url | Yes | Back view image of the subject (upload or public URL). |
| left_image_url | Yes | Left view image of the subject (upload or public URL). |
| seed | No | Set for reproducibility; leave empty for random. |
| num_inference_steps | No | Quality/speed trade-off (default: 50). |
| guidance_scale | No | Generation strength (default: 7.5). |
| octree_resolution | No | Mesh detail level (default: 256). |
| textured_mesh | No | Generate textured mesh instead of white mesh (3x price). |
| Output Type | Price |
|---|---|
| White mesh | $0.01 |
| Textured mesh | $0.03 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai//api/v3/wavespeed-ai/hunyuan3d-v2-multi-view 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 Multi View below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai//api/v3/wavespeed-ai/hunyuan3d-v2-multi-view" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"seed": 0,
"num_inference_steps": 50,
"guidance_scale": 7.5,
"octree_resolution": 256,
"textured_mesh": false
}'
# 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-multi-view", {
"seed": 0,
"num_inference_steps": 50,
"guidance_scale": 7.5,
"octree_resolution": 256,
"textured_mesh": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/hunyuan3d-v2-multi-view",
{
"seed": 0,
"num_inference_steps": 50,
"guidance_scale": 7.5,
"octree_resolution": 256,
"textured_mesh": false
}
)
print(output["outputs"][0]) # → URL of the generated outputHunyuan3d v2 Multi View is a WaveSpeedAI model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Hunyuan3D V2 Multi-View is Tencent's image-to-3D generative model on WaveSpeedAI that builds 3D reconstructions from multi-view images. 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-multi-view.
Hunyuan3d v2 Multi View starts at $0.010 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: `seed`, `guidance_scale`, `num_inference_steps`, `back_image_url`, `front_image_url`, `left_image_url`. 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-multi-view.
Average end-to-end generation time on WaveSpeedAI is around 428 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.