---
license: other
license_name: tencent-hy-community-license
license_link: LICENSE
pipeline_tag: image-text-to-text
library_name: mlx
tags:
- mlx
- hunyuan_vl_mot
- embodied-ai
---

# HY-Embodied-0.5 — bf16 MLX

BF16 MLX conversion of
[tencent/HY-Embodied-0.5](https://huggingface.co/tencent/HY-Embodied-0.5),
a 3.79B mixture-of-transformers embodied VLM, running natively on Apple
Silicon. This is the reference every measurement in the quantization
ladder was made against: it matches the pinned upstream implementation
token-for-token over the committed golden fixtures, in both thinking
modes. These weights require the from-scratch MLX implementation of the
`hunyuan_vl_mot` architecture published alongside them:
[hy-embodied-mlx](https://huggingface.co/vimalnakrani/hy-embodied-mlx). No other public runtime supports this
architecture.

## What was modified

BF16 safetensors converted to MLX layout; auto_map removed; nothing
quantized.

## Measured

| | weights | decode tok/s | Where2Place no-think | Where2Place think |
|---|---|---|---|---|
| this repo (bf16) | 7.05 GiB | 66.8 | 0.696 [0.600, 0.778] | 0.690 [0.593, 0.772] |

Text-only probe (50 scripted prompts): 0.700 [0.562, 0.809] no-think,
0.900 [0.786, 0.957] think.

Brackets are Wilson 95% intervals (n=100 pointing, n=50 probe). Measured
on an M3 Max (36 GB), greedy decoding; per-question CSVs, statistical
addendum, and one-command reproduction live in the implementation repo.
Quantized variants measured against this reference:
[8-bit](https://huggingface.co/vimalnakrani/HY-Embodied-0.5-8bit-mlx),
[6-bit](https://huggingface.co/vimalnakrani/HY-Embodied-0.5-6bit-mlx),
[5-bit](https://huggingface.co/vimalnakrani/HY-Embodied-0.5-5bit-mlx),
[4-bit](https://huggingface.co/vimalnakrani/HY-Embodied-0.5-4bit-mlx).

All variants and the runtime are collected at
[https://huggingface.co/collections/vimalnakrani/hy-embodied-05-mlx-6a550eb39f59d2adf90c0355](https://huggingface.co/collections/vimalnakrani/hy-embodied-05-mlx-6a550eb39f59d2adf90c0355).

The "Use this model" snippet Hugging Face auto-generates for MLX repos
(mlx-vlm) does not support this architecture; the Usage section below is
the working path.

## Usage

```python
from PIL import Image
from transformers import AutoTokenizer
from hy_embodied_mlx.model import load, generate
from hy_embodied_mlx.pointing import FORMAT_INSTRUCTION
from hy_embodied_mlx.processor import Processor

model_dir = "HY-Embodied-0.5-bf16-mlx"
tok = AutoTokenizer.from_pretrained(model_dir)
model = load(model_dir)
messages = [{"role": "user", "content": [
    {"type": "image"},
    {"type": "text", "text": f"Point to the red mug in the image. {FORMAT_INSTRUCTION}"},
]}]
inputs = Processor(tok)(messages, images=[Image.open("desk.jpg")])
print(tok.decode(generate(model, inputs, max_tokens=128)))
```

Pointing needs the format instruction shown — a bare "point to X" gets a
prose location description. Emitted coordinates are integers in 0-1000,
normalized to the preprocessed canvas (Tencent's documentation does not
specify the frame; for images whose dimensions are multiples of 32 and
within the 2048x2048 pixel budget, the canvas is pixel-identical to the
input image). Thinking mode is controlled with
`enable_thinking=True/False` on the chat template.

## License

These weights are a Model Derivative of Tencent HY, distributed under the
**Tencent HY Community License** (full text in the LICENSE file; NOTICE
included). This is not an open-source license. The obligations and
restrictions pass through to you:

- Territory: the license does not grant rights in the European Union, the
  United Kingdom, or South Korea.
- The Section 5(a) acceptable-use restrictions and the Section 5(b)
  restriction — including not using this model or its outputs to improve
  any other AI model — apply to these weights and anything you build on
  them.
- If you redistribute these weights or derivatives of them, include a copy
  of the license agreement, the NOTICE file, and a prominent statement of
  what you modified.

These Model Derivatives are distributed by the Hugging Face account
`vimalnakrani`. This repository is an independent conversion and is not
affiliated with, sponsored, or endorsed by Tencent.