Self-hosted model comparison · Checked October 30, 2026
Hunyuan3D-2.1 vs TRELLIS.2: Which Open-Source Image-to-3D Model Should You Use?
Check the license before the GPU. Hunyuan3D-2.1 is distributed under a territory-limited Community License; TRELLIS.2 releases its model and code under MIT. Neither repository includes free hosted generation. Choose according to your permitted use, available hardware and the output you can validate.
The phrase “open-source” in the question does not make these two licenses equivalent. This is a documentation comparison, not a speed, quality or printing benchmark.
License: the first decision
| Check | Hunyuan3D-2.1 | TRELLIS.2 |
|---|---|---|
| Primary license | Tencent Hunyuan 3D 2.1 Community License. Its territory excludes the European Union, United Kingdom and South Korea. | MIT for model and code. Retain the required copyright and license notices. |
| Other conditions | Redistribution, attribution and commercial-scale conditions apply. Read the complete agreement for your intended use. | Bundled or installed components can have separate terms; the README specifically identifies third-party renderer licenses. |
Sources: Hunyuan3D-2.1 license, TRELLIS.2 MIT license and TRELLIS.2 dependency notes. A license for code or weights does not clear rights in somebody else’s input image.
GPU: compare the documented workload
| Model | Official memory / environment evidence | What to verify locally |
|---|---|---|
| Hunyuan3D-2.1 | The README states 10 GB VRAM for shape, 21 GB for texture, and 29 GB for the combined workflow. | Which stages you need, available memory after other processes, and dependencies for that revision. |
| TRELLIS.2 | Linux-tested code; NVIDIA GPU with at least 24 GB memory. A100/H100 are verified configurations; CUDA Toolkit 12.4 is recommended. | Driver and compiler compatibility, attention backend, resolution and peak memory for your input. |
Sources: Hunyuan3D-2.1 README and TRELLIS.2 installation notes. These figures describe different pipelines, not an equivalent-output memory benchmark. We have not verified a smaller-GPU configuration.
Cost: open weights still use compute
There is no universal cost per usable asset. Local hardware has electricity and ownership costs; rented hardware has an hourly charge. Include installation, weight downloads, retries, storage and cleanup rather than pricing only a successful inference.
Planning formula: rental rate per hour × billed hours + storage and transfer charges. Divide total spend by the number of outputs that pass your acceptance checks. This is a budgeting method, not a measured price for either model.
Decide whether you need shape alone or shape plus texture.
Check the documented Linux / NVIDIA setup and the GLB export example.
Validate the exported asset before choosing
Hunyuan3D-2.1’s README describes shape and texture generation; the exact local export extensions were not verified here. TRELLIS.2’s example exports GLB. A documented export path does not establish that every material, mesh or physical scale will satisfy your application. Reopen your output and check the hidden sides, disconnected parts and material handling.
For a printing task, use the downloaded-STL checklist after obtaining compatible geometry. Neither the memory specification nor a convincing render proves watertightness or adequate walls.
If you do not want to manage a GPU, compare the hosted image-to-3D workflows. Image3D’s browser workflow is a separate service; this page does not announce an integration of either repository.