---
title: tripo_splat_mlx
canonical_url: "https://www.modelscope.cn/models/mlx-community/tripo_splat_mlx"
md_url: "https://www.modelscope.cn/models/mlx-community/tripo_splat_mlx.md"
repository: mlx-community/tripo_splat_mlx
last_updated: 2026-07-26
license: other
pipeline_tag: image-to-3D
tasks:
  - image-to-3D
parameters: 1.8B
tensor_type:
  - F32
  - I64
  - BF16
  - F16
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 152
stars: 0
tags:
  - mlx
  - triposplat
  - 3d-gaussian-splatting
  - image-to-3d
  - apple-silicon
---

# tripo_splat_mlx

> tripo_splat_mlx - mlx-community 在 ModelScope 开源的模型。MLX-native implementation of TripoSplat for Apple Silicon.

mlx-community/tripo_splat_mlx 是 ModelScope 魔搭社区上的 1.8B 参数image-to-3D模型，采用 other 许可。

- **Repository**: mlx-community/tripo_splat_mlx
- **License**: other
- **Tasks**: image-to-3D
- **Parameters**: 1.8B
- **Tags**: mlx, triposplat, 3d-gaussian-splatting, image-to-3d, apple-silicon
- **Downloads**: 152
- **Stars**: 0
- **Last updated**: 2026-07-26

Source: https://www.modelscope.cn/models/mlx-community/tripo_splat_mlx

---

# TripoSplat MLX

MLX-native implementation of [TripoSplat](https://github.com/VAST-AI-Research/TripoSplat) for Apple Silicon.

Part of **TripoFlux MLX** — a full MLX / CoreML accelerated text-to-3D pipeline
(**FLUX.2-klein-9B → BiRefNet → TripoSplat → .ply / .splat / .spz**) with an R3F web UI
featuring a [Looking Glass](https://lookingglassfactory.com/) holographic WebXR preview.

## Demo

[![LKG WebXR holographic preview demo](https://huggingface.co/Jup33QE/tripoflux-mlx/resolve/main/docs/demo-cover.png)](https://www.bilibili.com/video/BV1bFge6qEK2)

📺 [Bilibili video: Looking Glass (LKG) WebXR holographic preview demo](https://www.bilibili.com/video/BV1bFge6qEK2)

This repository contains MLX ports of the TripoSplat submodules:

- **`mlx_models/dinov3_mlx.py`** — DinoV3 ViT-H/16+ image encoder
- **`mlx_models/flux2vae_mlx.py`** — Flux2 VAE encoder
- **`mlx_models/flow_mlx.py`** — LatentSeqMMFlowModel (24-block multimodal flow transformer)

The original TripoSplat decoder (`OctreeGaussianDecoder`) remains on PyTorch MPS due to its complex dynamic sampling logic.

## Weights

| File | Size | Description |
|------|------|-------------|
| `dino_v3_vit_h.safetensors` | 1.6 GB | DinoV3 ViT-H/16+ image encoder |
| `flux2-vae.safetensors` | 336 MB | Flux2 VAE encoder |
| `triposplat_fp16.safetensors` | 741 MB | LatentSeqMMFlowModel (flow transformer) |
| `triposplat_vae_decoder_fp16.safetensors` | 576 MB | TripoSplat VAE decoder |
| `birefnet.safetensors` | 444 MB | BiRefNet background removal |

## License

This is a **mixed-license repository**. The most restrictive artifact determines
what the repository as a whole can be used for — with `flux2-vae.safetensors`
included, the repo as a whole is **non-commercial only**.

### ⛔ Non-commercial — separate restriction

| File | Upstream | License | Terms |
|------|----------|---------|-------|
| `flux2-vae.safetensors` | [black-forest-labs/FLUX.2-klein-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-9B) | **FLUX Non-Commercial License** | Weights are gated upstream. Commercial use of the weights or their outputs requires a paid license from Black Forest Labs. If you need a fully permissive stack, delete this file and load the VAE from the upstream gated repo at runtime after accepting its terms. |

### ⚠️ Custom permissive license — attribution required on redistribution

| File | Upstream | License | Terms |
|------|----------|---------|-------|
| `dino_v3_vit_h.safetensors` | [facebook/dinov3](https://github.com/facebookresearch/dinov3) | **DINOv3 License** | Commercial use **is allowed**, but any redistribution of copies or derivatives must include the DINOv3 License text. Upstream downloads are gated and unavailable in sanctioned jurisdictions. |

### ✅ MIT — permissive core

| File | Upstream | License |
|------|----------|---------|
| `triposplat_fp16.safetensors` | [VAST-AI/TripoSplat](https://huggingface.co/VAST-AI/TripoSplat) | MIT |
| `triposplat_vae_decoder_fp16.safetensors` | [VAST-AI/TripoSplat](https://huggingface.co/VAST-AI/TripoSplat) | MIT |
| `birefnet.safetensors` | [ZhengPeng7/BiRefNet](https://huggingface.co/ZhengPeng7/BiRefNet) | MIT |
| `mlx_models/*.py` | this repo (MLX port) | MIT |

The MLX port code in `mlx_models/` is released under the
[MIT License](https://opensource.org/licenses/MIT), same as the main project:
[https://github.com/Jup33Q/tripoflux-mlx](https://github.com/Jup33Q/tripoflux-mlx).

## Usage

```python
from mlx_models.dinov3_mlx import DinoV3ViT
from mlx_models.flux2vae_mlx import Flux2VAEEncoder
from mlx_models.flow_mlx import LatentSeqMMFlowModel

# Load models
dino = DinoV3ViT()
dino.load_safetensors("dino_v3_vit_h.safetensors")

vae = Flux2VAEEncoder()
vae.load_safetensors("flux2-vae.safetensors")

flow = LatentSeqMMFlowModel(
    q_token_length=8192, in_channels=16, cam_channels=5, out_channels=16,
    model_channels=1024, cond_channels=1280, cond2_channels=128,
    num_refiner_blocks=2, num_blocks=24, num_heads=16, mlp_ratio=4,
    qk_rms_norm=True, share_mod=True, use_shift_table=True,
)
flow.load_safetensors("triposplat_fp16.safetensors")
```

## Full Pipeline

For the complete text-to-3D pipeline (FLUX.2-klein-9B → BiRefNet → TripoSplat → SPZ export), see the main project:
[https://github.com/Jup33Q/tripoflux-mlx](https://github.com/Jup33Q/tripoflux-mlx)

- R3F web UI with splat viewport, SSE progress streaming, and Looking Glass WebXR preview
- SPZ-canonical exports (`.spz` / `.ply` / `.splat`)
- TripoSplat sampler steps selectable (20 / 24 / 28)
- Mirror on ModelScope: [Jup33Q/TripoSplat-MLX](https://modelscope.cn/models/Jup33Q/TripoSplat-MLX)