Best Image to 3D Models on HuggingFace (2026)

Last updated: April 11, 2026

The best image-to-3D models on HuggingFace in 2026 are TRELLIS.2-4B (best for production-grade PBR assets), Hunyuan3D 2.1 (best for high-fidelity textures), Hi3DGen (best geometric quality), and Stable Fast 3D (best for speed at under 1 second). We tested every major model on the same set of reference images and compared generation speed, output quality, hardware requirements, and licensing.

Why HuggingFace for Image-to-3D?

HuggingFace has become the central hub for open-source image-to-3D models. Every major research lab — Microsoft, Tencent, Stability AI, NVIDIA, Meta, and ByteDance — publishes their models there. As of April 2026, the image-to-3D model category lists dozens of models with thousands of community-created Spaces for testing them without writing code.

The advantage of HuggingFace over commercial platforms: you can run models locally, fine-tune them on your own data, integrate them into custom pipelines, and avoid per-generation costs. The trade-off is that you need GPU hardware and technical knowledge to deploy them.

This guide ranks the top models, provides real benchmark data, and helps you choose the right one for your use case.

Top Image-to-3D Models Ranked

1. Microsoft TRELLIS.2-4B — Best Overall Quality

microsoft/TRELLIS.2-4B | 746 Likes | MIT License

TRELLIS.2 is Microsoft's second-generation image-to-3D model and the current leader for balanced quality across geometry, texture, and speed.

Key specs:

What makes it stand out:

TRELLIS.2 introduces O-Voxel (field-free sparse voxel representation) and SC-VAE (16x spatial compression), which means it generates detailed geometry without the computational overhead of implicit neural fields. The flow-matching DiT architecture produces cleaner topology than most competitors.

The PBR material output is production-ready — you get separate Base Color, Metallic, Roughness, and Opacity maps. This is rare among open-source models and makes the output directly usable in game engines and 3D software without additional texturing work.

Known limitations:

• Raw meshes may have small holes that need repair before 3D printing
• Not aligned to human preference through RLHF — aesthetic quality can vary
• Requires high-end GPU for full-resolution generation

Best for: Game development, product visualization, and anyone who needs production-quality PBR assets without post-processing textures.

2. Tencent Hunyuan3D 2.1 — Best for Texture Fidelity

tencent/Hunyuan3D-2.1 | 888 Likes | Tencent Community License

Hunyuan3D 2.1 is Tencent's latest open-source model, featuring a two-stage pipeline: Hunyuan3D-DiT for shape generation and Hunyuan3D-Paint for texture synthesis.

Key specs:

What makes it stand out:

Hunyuan3D 2.1 generates production-grade PBR materials — Base Color, Normal, Roughness, Metallic, and Ambient Occlusion maps. Its geometry accuracy is reported to be 10x better than version 2.0. The model supports both single-image and multi-view input, giving you more control when you have multiple angles of an object.

In the Hunyuan3D 2.0 paper benchmarks (which still apply as a baseline), this model family outperformed all open-source and closed-source baselines on CMMD, FID, and CLIP-score metrics.

Known limitations:

• Slow: median generation time of ~139 seconds is 5-40x slower than competitors
• High VRAM requirements for full pipeline (29GB)
• Community license has usage conditions (check before commercial deployment)

Best for: High-fidelity asset creation where texture quality is critical — e-commerce product visualization, architectural visualization, and VFX reference models.

3. Hi3DGen — Best Geometric Quality

Stable-X/Hi3DGen | MIT License | ICCV 2025

Hi3DGen is a newer model that uses Normal Bridging — leveraging normal maps as an intermediate representation to achieve superior geometric quality.

Key specs:

What makes it stand out:

Community testers consistently rate Hi3DGen as producing the best geometric quality among open-source models. The Normal Bridging approach estimates surface normals from the input image first, then uses those normals to guide 3D reconstruction. This results in sharper edges, better surface detail, and fewer geometric artifacts than models that predict geometry directly.

The model was accepted at ICCV 2025, confirming its academic rigor. It's also fully MIT licensed.

Known limitations:

• Parameter count and training details are not fully disclosed
• Pipeline is more complex (multi-stage)
• Relatively new — less community testing and fewer Spaces than TRELLIS or Hunyuan3D
• Requires more VRAM than fast-generation models

Best for: Applications where geometric precision matters most — technical models, CAD-adjacent workflows, and assets that will undergo further sculpting.

4. Stable Fast 3D — Best for Speed

stabilityai/stable-fast-3d | 743 Likes | Stability AI Community License

Stable Fast 3D (SF3D) is Stability AI's speed-optimized model. It generates a UV-unwrapped textured mesh with material parameters in under 0.5 seconds.

Key specs:

What makes it stand out:

At 0.5 seconds per generation, SF3D is the fastest model that produces usable textured output. It also handles de-lighting — removing lighting artifacts from the input image — which means the output textures are cleaner and more suitable for re-lighting in game engines or 3D software.

The low VRAM requirement (6GB) means it runs on consumer-grade GPUs like the RTX 3060 or RTX 4060.

Known limitations:

• Lower polygon count than TRELLIS or Hunyuan3D
• Commercial use requires enterprise license if your annual revenue exceeds $1M
• Less detail in complex geometry compared to slower models

Best for: Rapid prototyping, real-time applications, batch processing of large image sets, and developers with limited GPU resources.

5. TripoSR — Best for Low Hardware Requirements

stabilityai/TripoSR | 607 Likes | 117K Monthly Downloads | MIT License

TripoSR was the model that popularized fast image-to-3D generation. While newer models have surpassed it in quality, it remains the most downloaded image-to-3D model on HuggingFace.

Key specs:

What makes it stand out:

TripoSR is the most accessible image-to-3D model. It runs on any GPU with 6-8GB VRAM, uses the permissive MIT license, and has the largest community ecosystem with 100+ HuggingFace Spaces. The training methodology (LRM architecture trained on a large-scale dataset) makes it reliable for simple objects.

Known limitations:

• Output mesh quality is considered "average" by 2026 standards
• Low polygon count compared to newer models
• No PBR material output
• Less detail on complex or organic shapes

Best for: Quick previews, educational projects, developers getting started with image-to-3D, and anyone with limited GPU hardware.

6. ByteDance Seed3D — Best for Simulation-Grade Output

Seed3D | Online Service | arXiv:2510.19944

Seed3D is ByteDance's entry into image-to-3D, producing simulation-grade 3D assets with precise geometry and aligned textures.

Key specs:

What makes it stand out:

Seed3D prioritizes quality over speed. Its output is designed to meet simulation requirements — meaning the geometry is watertight, textures are physically accurate, and the overall quality approaches hand-crafted models. For applications where physical accuracy matters (engineering, simulation, automotive), this is a strong choice.

Known limitations:

• Very slow: 5-30 minutes per generation
• Not fully open-source (weights not available for local deployment)
• Limited to online service access

Best for: Engineering and simulation applications where physical accuracy is more important than speed.

7. NVIDIA Asset Harvester — Best for Specialized Use Cases

nvidia/asset-harvester | NVIDIA Open Model License

Asset Harvester is NVIDIA's specialized model for generating 3D assets from real-world images for simulation environments.

Key specs:

What makes it stand out:

Asset Harvester handles occlusion, noise, and extreme viewpoint bias — common challenges in real-world photography. It generates 16 novel viewpoints via a multi-view diffusion model, then reconstructs 3D Gaussians. The output integrates directly with NVIDIA Omniverse.

Known limitations:

• Requires 30GB+ VRAM (A100/H100 only)
• Specialized for automotive/driving scenarios
• Low community adoption (18 likes, 131 monthly downloads)
• Output format (3DGS) is not a traditional mesh

Best for: Autonomous driving simulation and NVIDIA Omniverse workflows. Not recommended for general-purpose 3D generation.

Quick Comparison Table

How to Choose the Right Model

By Use Case

By Hardware

By License Requirements

How to Test These Models Without a GPU

You don't need expensive hardware to try these models. HuggingFace Spaces lets you test them for free in your browser:

Each Space provides a web interface where you upload an image and receive a downloadable 3D model. Generation times in Spaces are typically slower than local deployment due to queue times.

For the fastest experience without any setup, you can also use cloud-based tools:

Generate a 3D model from your image now — powered by TRELLIS architecture, no downloads required.

Emerging Models to Watch

The image-to-3D field is evolving rapidly. These models were released recently or are gaining traction:

• Meta MapAnything (1B parameters): A unified Transformer supporting 12+ 3D reconstruction tasks. Published January 2026, accepted at 3DV 2026. Currently non-commercial (CC-BY-NC-4.0).
• Depth Anything V3: ByteDance Seed's unified visual geometry model. Not a direct image-to-3D tool, but its depth estimation powers many 3D reconstruction pipelines.
• Hunyuan3D 3.0 (Pro): Tencent's latest iteration beyond 2.1, with further quality improvements. Details still emerging.

FAQ

Which image-to-3D model is best for beginners?

TripoSR is the best starting point. It's MIT licensed, runs on 6-8GB VRAM, has the largest community (117K monthly downloads, 100+ Spaces), and generates results in under a second. The quality won't match TRELLIS.2 or Hunyuan3D, but it's the fastest way to start experimenting.

Can I use these models commercially?

TRELLIS.2, TripoSR, and Hi3DGen are MIT licensed — commercial use is fully allowed with no restrictions. SF3D is free for businesses with under $1M annual revenue. Hunyuan3D uses the Tencent Community License, which allows commercial use with specific conditions. Always verify the license on the model's HuggingFace page before deploying commercially.

Do I need to run these models locally?

No. You can test all of them through HuggingFace Spaces (free, browser-based). For production use, cloud platforms like ours handle the GPU infrastructure for you. Local deployment gives you more control and avoids per-generation costs, but requires significant GPU hardware.

How do these compare to commercial tools like Meshy or Tripo AI?

Commercial tools typically build on top of these open-source models (or similar architectures) and add features like auto-rigging, batch processing, API access, and better UI. The raw model quality is similar, but commercial tools are easier to use and don't require technical knowledge. If you need a simple workflow, try Trellis2 — it runs TRELLIS-based generation in the cloud with a point-and-click interface.

What resolution should my input image be?

Most models expect 512x512 input. TRELLIS.2 and Hunyuan3D can handle higher resolutions. For best results, use a clearly defined subject on a clean background at 512x512 or higher. See our complete image preparation guide for detailed tips.

Conclusion

The HuggingFace image-to-3D ecosystem in 2026 offers something for every use case and hardware level:

• Best overall: TRELLIS.2-4B for production-grade PBR assets with MIT licensing
• Best textures: Hunyuan3D 2.1 for the highest-fidelity texture and PBR material output
• Best geometry: Hi3DGen for precise geometric reconstruction
• Best speed: Stable Fast 3D for sub-second generation on consumer hardware
• Best for learning: TripoSR for its low barrier to entry and massive community

If you want to skip the setup and generate 3D models directly from your browser, try Trellis2 — cloud-based TRELLIS generation with no GPU required.

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Related articles:

• How to Turn an Image into a 3D Model: step-by-step tutorial for converting photos to 3D
• How to Use TRELLIS 2: complete guide to using TRELLIS 2 for image-to-3D and text-to-3D generation
• What is TRELLIS 3D?: deep dive into the AI architecture behind image-to-3D generation
• Best Free OBJ Viewers in 2026: tools for previewing your exported 3D models