Two official open versions
Hunyuan3D-2 and Hunyuan3D-2.1 both ship Hugging Face Spaces and model repositories under the tencent org.
Meshy AI: Plataforma de modelado 3D con IA. Genera, texturiza y exporta assets 3D en minutos.
Tencent Hunyuan · Open image-to-3D
Tencent open image-to-3D — Hunyuan3D-2 and production-oriented 2.1 with PBR
Hunyuan3D is Tencent’s open family of systems that turn images (and related inputs) into textured 3D meshes. This single landing covers both Hunyuan3D-2 and Hunyuan3D-2.1—so you can understand version roles and jump into either official Hugging Face demo.
Hunyuan3D-2 is published on Hugging Face as an image-to-3D / text-to-3D stack (model tags include arXiv:2501.12202 and arXiv:2411.02293). It is widely used in the open community as a two-stage shape + texture style pipeline with official Gradio Spaces.
Hunyuan3D-2.1 is described in “Hunyuan3D 2.1: From Images to High-Fidelity 3D Assets with Production-Ready PBR Material” (arXiv:2506.15442). Official materials emphasize two foundations: Hunyuan3D-DiT for shape generation (flow-based diffusion + shape VAE) and Hunyuan3D-Paint for multi-view PBR materials (e.g. albedo / metallic / roughness channels), plus broader open-sourcing of weights and training code versus earlier texture RGB pipelines.
We intentionally do not split 2.0 and 2.1 into separate landings: product-wise they are one series. The playground embeds both Spaces as tabs so you can A/B the live demos.
Use Hunyuan3D when you want a mature Tencent open pipeline for image-to-3D meshes and textures—especially 2.1 if you care about production-oriented PBR materials and open training/finetune paths documented in the 2.1 technical report.
STEP 1
Start from a single object image in the Space UI. Model cards also tag text-to-3D capability depending on the deployed pipeline.
STEP 2
Hunyuan3D-2.1’s shape path combines a flow-based diffusion transformer with a high-fidelity mesh autoencoder (Hunyuan3D-ShapeVAE per the report).
STEP 3
Texture models synthesize view-consistent appearance; 2.1’s Paint stage targets multi-channel PBR maps rather than simple RGB bake-only looks.
Hunyuan3D-2 and Hunyuan3D-2.1 both ship Hugging Face Spaces and model repositories under the tencent org.
2.1 docs describe Hunyuan3D-DiT for geometry and Hunyuan3D-Paint for mesh-conditioned multi-view PBR synthesis.
The 2.1 report highlights physics-grounded PBR maps (e.g. metallic reflections) replacing earlier RGB-only texture painting approaches.
Diffusers-tagged weights, bilingual model cards (en/zh), and large Space traffic make Hunyuan3D a common open baseline.
Figures below come from the linked papers, model cards, or project pages—not from unbenchmarked third-party marketing claims.
Quick textured meshes for level blockouts, avatar props, and AR product previews.
2.1 materials stress full weights and training code for community finetunes and industrial adaptation.
When metallic/roughness style maps matter more than pure silhouette reconstruction.
Established open 2.x demo (HF: tencent/Hunyuan3D-2). Strong community adoption for image-to-3D meshes and textures; related papers tagged on the model card (arXiv:2501.12202, 2411.02293).
Updated open release focused on high-fidelity assets with production-oriented PBR materials (arXiv:2506.15442). Demo Space: tencent/Hunyuan3D-2.1.
Both demos are available as tabs on the playground—no separate landing pages for 2.0 vs 2.1.
They are successive open releases in the same Hunyuan3D product line. One landing avoids duplicate SEO pages while the playground still embeds both Spaces.
Per arXiv:2506.15442 and the official GitHub README, 2.1 emphasizes production-ready PBR material synthesis (Hunyuan3D-Paint) alongside shape generation (Hunyuan3D-DiT), with broader open-sourcing of training components.
Yes. Open the Hunyuan3D playground and switch tabs between Hunyuan3D 2.0 and 2.1 official Spaces.
Landing claims are grounded in the following primary materials. Always prefer the original paper or model card for citations.
Jump into the playground and generate a 3D model from your own image—no install required.