Instructions to use ChrisColeTech/hunyuan3d-v2-turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ChrisColeTech/hunyuan3d-v2-turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ChrisColeTech/hunyuan3d-v2-turbo", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Hunyuan3D-2 Turbo β draft-speed image-to-3D
The step-distilled turbo checkpoints from the Hunyuan3D-2 family, single-view and multi-view. β6β18 s per mesh on an RTX 5090 β fast enough to iterate on a subject interactively.
What this repo is: the
dit-v2-0-turbo(single-view) anddit-v2-mv-turbo(multi-view) shape checkpoints β weights only, not a retrain. The samples below were generated with the single-view turbo.
Samples
Single image in, mesh out. Source images were rendered with Z-Image Turbo; the
meshes are Blender Workbench clay renders of the raw .glb output.
![]() | ![]() |
| **source** β `a cute chunky retro robot toy standing upright, rounded metal body, simple friendly face, studio product photograph on a plain white background` | **mesh** β 0.72 MB `.glb`, generated in 18 s (incl. model load), seed 42 |
![]() | ![]() |
| **source** β `an ornate ceramic teapot with a curved spout and handle, glazed blue and white porcelain, studio product photograph` | **mesh** β 0.70 MB `.glb`, generated in 6 s, seed 42 |
Textured (img2mesh_textured)
The same robot through the full chain β turbo shape, then the paint stage β instead of shape alone.
![]() | ![]() |
| **`img2mesh`** β 0.72 MB, **18 s** | **`img2mesh_textured`** β 3.4 MB with a baked base-colour texture, **+67 s** for the paint stage |
Turntable
Four views, 90Β° apart.
Recommended settings
| Parameter | Production value | Meaning |
|---|---|---|
seed |
any | Deterministic per seed |
| input | one RGB(A) image | Centred subject, plain background (mv variant takes several views) |
| output | .glb |
Watertight triangle mesh, no texture |
Supported modes: img2mesh, txt2mesh (single-view turbo); img2mesh_mv (multi-view turbo); _textured variants via a separate paint stage
Notes and gotchas
- This is the draft tier. Meshes land around 0.7 MB where the larger models in this family return 10β38 MB for the same inputs. Silhouette, proportion and major features are captured; fine relief is smoothed away. Use it to iterate on framing and subject, then re-run a heavier model for the final asset.
- Two checkpoints ship here.
dit-v2-0-turbotakes one image;dit-v2-mv-turbotakes several views of the same subject and is the one to use when you have them β they are not interchangeable at the job level. - Output is untextured. Colour comes from a separate paint pipeline.
- Generated meshes come out facing the source image's front, so a fixed camera works across a batch.
Files
| Path | Size | Role |
|---|---|---|
split/fp16/turbo/hunyuan3d-dit-v2-0-turbo/model.fp16.safetensors |
4.6 GB | single-view turbo shape DiT β the samples above |
split/fp16/turbo/hunyuan3d-dit-v2-mv-turbo/model.fp16.safetensors |
4.6 GB | multi-view turbo shape DiT |
Each ships with its config.yaml alongside.
Provenance
- Upstream base model:
tencent/Hunyuan3D-2turbo checkpoints - This build: redistributed as a split component tree. Weights are not retrained here.
- License: Tencent Hunyuan3D community license β refer to upstream for redistribution and commercial-use terms.
- Downloads last month
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Model tree for ChrisColeTech/hunyuan3d-v2-turbo
Base model
tencent/Hunyuan3D-2





