Exe AI

Exe AI

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Exe Motion Dynamic V1 — local image-to-video for Apple Silicon

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 — no cloud, no upload of your images or prompts.

What was quantized

Bar chart: the text encoder shrinks from 46 GB in F32 to 12.5 GB in 8-bit, four times smaller

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. See the linked LICENSE for terms.

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