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license: other
license_name: ltx-2.3
license_link: https://huggingface.co/Lightricks/LTX-2.3/blob/main/LICENSE
base_model: Lightricks/LTX-2.3
library_name: mlx
pipeline_tag: image-to-video
language:
- en
tags:
- mlx
- video
- image-to-video
- text-to-video
- ltx
- apple-silicon
- 8-bit
- quantized
---
<p align="center">
<a href="https://exe-hq.net">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://huggingface.co/exeterminal/Exe-Motion-Dynamic-V1-MLX/resolve/main/exe-ai-logo-dark.png">
<source media="(prefers-color-scheme: light)" srcset="https://huggingface.co/exeterminal/Exe-Motion-Dynamic-V1-MLX/resolve/main/exe-ai-logo-light.png">
<img src="https://huggingface.co/exeterminal/Exe-Motion-Dynamic-V1-MLX/resolve/main/exe-ai-logo-light.png" width="480" alt="Exe AI: AI systems reimagined.">
</picture>
</a>
</p>
<p align="center"><a href="https://exe-hq.net"><b>exe-hq.net</b></a></p>
---
<div align="center">
<img src="exe-motion-dynamic-hero.png" alt="Exe Motion Dynamic V1 — local image-to-video for Apple Silicon" width="100%">
</div>
# Exe Motion Dynamic V1
The video model of **Exe Motion**, built to run local on an Apple Silicon Mac.
It is **LTX-2.3 (22B distilled)** with one change that matters on a 64 GB
machine: the text encoder is quantized to **8-bit**, so the part that used to
be the memory spike of a run is now a quarter of its size.
**Website to the Main AI Agent Harness: https://exe-hq.net**
Everything runs on-device through [MLX](https://github.com/ml-explore/mlx) — no
cloud, no upload of your images or prompts.
## What was quantized
<div align="center">
<img src="exe-motion-dynamic-quant.png" alt="Bar chart: the text encoder shrinks from 46 GB in F32 to 12.5 GB in 8-bit, four times smaller" width="80%">
</div>
The Gemma text encoder shipped in **F32** and, at ~46 GB, was the biggest single
thing a run had to hold. It is loaded, used to read the prompt, then freed
before the transformer runs — so its size sets the peak. Quantizing it to 8-bit
takes it to **12.5 GB**, resident, without touching the transformer.
| Part | Before | After |
|---|---:|---:|
| Text encoder (Gemma) | 46 GB · F32 | **12.5 GB · 8-bit** |
| Transformer (22B distilled) | 35 GB | 35 GB · unchanged |
| Whole model on disk | ~89 GB | **~55 GB** |
The transformer is left at full precision on purpose: the runtime has no
quantized path for it, and a quantized copy would not load. The encoder is where
the win is, and it is the honest one.
## What it does
Image-to-video and text-to-video at up to 720p. Frame count drives the length
(24 fps); resolution is free in steps of 64. A distilled fast path keeps steps
low; there is no separate turbo weight to install.
## Recommended settings
- **Resolution**: 1280×704 is the default; drop it for longer clips or to save
memory.
- **Frames**: `8n+1` (81 ≈ 3.4 s, 121 ≈ 5 s). Longer needs more memory.
- **Apple Silicon**: long runs on a 64 GB machine still benefit from raising the
Metal working-set limit before starting:
`sudo sysctl iogpu.wired_limit_mb=59392`.
## Files
A whole, assembled build — nothing to convert or borrow:
```
transformer/ 22B distilled, bf16
text_encoder/ Gemma, 8-bit (this build's change)
text_projections/ connectors
vae/ audio_vae/ vocoder/ tokenizer/
```
## License
Weights inherit the license of the base model,
[Lightricks/LTX-2.3](https://huggingface.co/Lightricks/LTX-2.3). See the linked
LICENSE for terms.
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