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.
Bereit
$0.16pro Durchlauf·~62 / $10











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.
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 | $0.16 |
| Model | Price | Best For |
|---|---|---|
| Hunyuan3D V2 Mini | $0.10 | Quick prototypes, icons, simple objects |
| Hunyuan3D V2 Base | $0.16 | Production assets, detailed models |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/hunyuan3d/v2-base with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read URLs from data.outputs. Examples for Hunyuan3d v2 Base below.
# Submit the prediction
curl --fail-with-body --connect-timeout 10 --max-time 60 \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/hunyuan3d/v2-base" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"image": "https://example.com/your-input.jpg"
}'
# Wait at least 2 seconds, then poll. Safe GET requests may be retried.
curl --fail-with-body --connect-timeout 10 --max-time 30 \
--retry 4 --retry-all-errors --retry-delay 1 \
-X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# Start at 2 seconds and increase the interval for long-running tasks.
# Stop on completed, failed, cancelled, or timeout.// npm install wavespeed
const { Client } = require('wavespeed');
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
const client = new Client(apiKey);
try {
const result = await client.run("wavespeed-ai/hunyuan3d/v2-base", {
"image": "https://example.com/your-input.jpg"
}, {
timeout: 3600,
pollInterval: 2.0,
});
console.log(result.outputs);
} catch (error) {
console.error('Generation failed:', error);
process.exitCode = 1;
}# pip install wavespeed
import os
from wavespeed import Client
client = Client(api_key=os.environ["WAVESPEED_API_KEY"])
try:
output = client.run(
"wavespeed-ai/hunyuan3d/v2-base",
{
"image": "https://example.com/your-input.jpg"
},
timeout=3600.0,
poll_interval=2.0,
)
print(output["outputs"])
except Exception as error:
raise SystemExit(f"Generation failed: {error}") from errorHunyuan3d v2 Base is a WaveSpeedAI model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. 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. 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/hunyuan3d-v2-base.
Hunyuan3d v2 Base starts at $0.16 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-base.
Average end-to-end generation time on WaveSpeedAI is around 700 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.