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ddalcu/Hunyuan3D-2.1-MLX-Serve-8bit
Hunyuan3D-2.1-MLX-Serve-8bit is a image-to-3d model from ddalcu. Use it for the image-to-3d task on the model card, and read the license before you ship it in a product. It is set up for mlx-serve. The card lists the license as other.
Photo → textured, rigged 3D model — fully on-device on Apple Silicon. This is the complete 3D generation stack for mlx-serve / MLX Core, converted to MLX-native safetensors and quantized to 8-bit (group size 64), pack…
Downloads · 30 days
571
27% of all-time downloads
All-time downloads
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8.7 GB
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.safetensors8.7 GB · 100%
From the Hugging Face model README
Photo → textured, rigged 3D model — fully on-device on Apple Silicon. This is the complete 3D generation stack for mlx-serve / MLX Core, converted to MLX-native safetensors and quantized to 8-bit (group size 64), packaged as one repo so the app downloads one thing:
| Stage | Where | Contents | Source |
|---|---|---|---|
| Shape (image → mesh) | repo root | dit.safetensors (3.3B MoE flow-match DiT), conditioner.safetensors (DINOv2-Large), vae.safetensors (ShapeVAE decoder + geo-decoder) | tencent/Hunyuan3D-2.1 |
| Texture (full PBR paint) | paint/ | unet.safetensors (2.5D multiview UNet), unet_dual.safetensors (reference stream), vae.safetensors (SD 2.x AutoencoderKL), dino.safetensors (DINOv2-giant) | tencent/Hunyuan3D-2.1 (hunyuan3d-paintpbr-v2-1) + facebook/dinov2-giant |
| Auto-rig (skeleton + skin) | unirig/ | skeleton.safetensors (UniRig stage-1 AR skeleton: michelangelo perceiver + OPT-350m decoder) | VAST-AI/UniRig |
Total ≈ 8.1 GB. Dense tensors are fp16; eligible linears are 8-bit affine-quantized.
The MLX Core app's 3D pane downloads this
automatically. With a standalone mlx-serve:
hf download ddalcu/Hunyuan3D-2.1-MLX-Serve-8bit --local-dir ~/.mlx-serve/models/ddalcu/Hunyuan3D-2.1-MLX-Serve-8bit
mlx-serve --serve --model-dir ~/.mlx-serve/models
curl http://localhost:8080/v1/3d/generations -H 'Content-Type: application/json' -d '{
"model": "ddalcu/Hunyuan3D-2.1-MLX-Serve-8bit",
"image": "<base64 PNG/JPEG>",
"texture": true,
"rig": true
}' # → {"format":"glb","data":"<base64 GLB>"} — a textured, rigged glTF binary
texture and rig are optional (shape-only is fastest); the server resolves the
paint/ and unirig/ stages from this repo's subdirectories automatically.
Converted with the scripts in the mlx-serve repo (tests/convert_hunyuan3d_weights.py,
tests/convert_hunyuan3d_paint_weights.py, tests/convert_unirig_weights.py). The
native Zig engines were validated against the PyTorch references with cosine-similarity
oracles: shape e2e SDF grid 0.9998, paint full-UNet denoise step 1.0000, UniRig greedy
skeleton decode token-exact. Structural transforms (per-head QKV de-interleaves, MoE
expert stacking, NCHW→OHWI conv layout) are baked out at convert time.
paint/LICENSE).conditioner.safetensors, paint/dino.safetensors): Apache-2.0 (Meta AI).unirig/NOTICE
for the code/weights licensing split.