If you've been following the open-source AI 3D space, three names keep coming up: TRELLIS from Microsoft Research, Hunyuan3D from Tencent, and Stable Fast 3D from Stability AI. All three are foundation models for image-to-3D generation, all three are open-sourced or have permissive research releases, and all three take radically different approaches to the same problem.
This comparison won't pretend there's a single winner. The right model depends on what you're building and what tradeoffs you can absorb. Let's walk through each one honestly.
Why This Comparison Matters
Closed-source services like Meshy and Tripo are great products, but if you want to understand how AI 3D generation actually works — or build on top of it — you need to look at the open foundation models. TRELLIS, Hunyuan3D, and Stable Fast 3D represent three distinct philosophies: structured latents, two-stage diffusion, and pure speed. Whatever a closed service is doing under the hood, it's almost certainly a variant or descendant of one of these three.
TRELLIS (Microsoft Research, late 2024)
TRELLIS introduced a structured latent representation that decouples geometry from appearance and supports multiple output formats from the same latent — Gaussian splats, meshes, and radiance fields. That flexibility is unusual. Most models commit to one representation and live with it; TRELLIS lets you decode whichever one fits your downstream tool.
The geometry quality is where TRELLIS really pulls ahead. Surfaces are crisp, topology is more usable out of the box, and concave details survive the generation process better than in competing models. The refined TRELLIS.2 release in 2025 tightened convergence, improved texture fidelity, and added better single-image priors for ambiguous viewpoints.
The catch: TRELLIS is heavier. VRAM usage runs in the 16–24 GB range for comfortable inference, and generation takes longer than the speed-optimized competitors. If you're building a real-time creative tool, that latency may be a problem. If you're producing assets that need to ship into a game engine, it's worth the wait.
For context: HiGen3D's photo-to-3D pipeline uses TRELLIS.2 internally, mostly because of the geometry quality and how well it handles vehicles — a category that historically breaks lesser models on subtle curvature and wheel wells.
Hunyuan3D (Tencent, 2024–25)
Hunyuan3D takes a two-stage diffusion approach: first a Diffusion Transformer (DiT) generates the shape, then a separate texture diffusion stage paints it. This separation has real benefits. The shape stage can focus entirely on geometry without being distracted by appearance, and the texture stage can be swapped or fine-tuned independently — useful if you want stylized vs. photorealistic outputs from the same shape backbone.
Hunyuan3D is particularly strong on real-world objects with rich textural detail: cluttered consumer products, food, fabric, and decorative items. The textures come out vivid and high-resolution, often beating TRELLIS on raw visual appeal even when TRELLIS wins on underlying geometry.
Where Hunyuan3D struggles a bit: structural symmetry on man-made objects (the seam where the two diffusion stages meet sometimes leaks into the final result), and the two-stage pipeline is slower than single-pass methods. License terms have also shifted across versions, so check the latest release notes if you're shipping it commercially.
Stable Fast 3D (Stability AI, 2024)
Stable Fast 3D is what its name suggests: speed-first. Inference happens in under a second on a modern GPU. That's not a typo — it's a fundamentally different design point from TRELLIS and Hunyuan3D, which think in tens of seconds or minutes.
To hit that speed, Stable Fast 3D trades fidelity. Geometry is softer, fine details get smoothed away, and textures are lower-resolution than the other two. It's not a finishing tool — it's an iteration tool. If you want to try fifty variations of a concept and pick the best, Stable Fast 3D's loop time is unbeatable. If you need a hero asset, you'll regenerate it with a slower model afterwards.
For a deeper look at how raw model speed actually changes a creative workflow, see our piece on sketch-to-3D with AI, where fast iteration is the whole point.
Comparison Axes
- Geometry quality: TRELLIS > Hunyuan3D > Stable Fast 3D
- Texture quality: Hunyuan3D > TRELLIS > Stable Fast 3D
- Speed: Stable Fast 3D (sub-second) ≫ TRELLIS (seconds) ≈ Hunyuan3D (seconds)
- VRAM: Stable Fast 3D (8 GB) < Hunyuan3D (12–16 GB) < TRELLIS (16–24 GB)
- Output formats: TRELLIS supports Gaussian / mesh / radiance fields; Hunyuan3D outputs textured mesh; Stable Fast 3D outputs textured mesh (GLB)
- License: All have permissive or research-friendly licenses, but commercial terms vary — read the current LICENSE for the version you're shipping
When to Use Each
- Game-ready hero assets, vehicles, anything that needs clean geometry: TRELLIS or TRELLIS.2.
- Photorealistic everyday objects, e-commerce, decorative items: Hunyuan3D.
- Rapid prototyping, concept exploration, real-time creative tools: Stable Fast 3D.
And, importantly: these aren't mutually exclusive. A serious pipeline might use Stable Fast 3D for ideation, then regenerate the winning concept with TRELLIS or Hunyuan3D for the final asset. See our AI 3D asset pipeline for indie devs for a worked example.
Where This Is Headed
The next wave is already visible. Multi-image conditioning — feeding the model several views of the same object — dramatically improves backside reconstruction, and TRELLIS.2 forks are already shipping it. Video-to-3D turns a short clip into a textured mesh, blurring the line between AI generation and classical photogrammetry. And native Gaussian Splatting outputs are growing — useful for NeRF-adjacent rendering even if your final delivery is a baked GLB.
If you want to skip the comparison and just generate something, HiGen3D's generator wraps TRELLIS.2 in a vehicle-tuned pipeline, or you can browse what others have made in the community gallery. For a broader market view including closed-source services, see our 2026 generator roundup.