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mlx-community/Macaw-OptiQ-4bit
Macaw-OptiQ-4bit is a text generation model from mlx-community. Use it when you need the model to write or continue text. It is set up for mlx. The card lists the license as other.
Built with mlx-optiq, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon, no PyTorch and no cloud. All OptiQ quants · Docs · LFM2.5 family
Downloads · 30 days
180
30% of all-time downloads
All-time downloads
591
Public
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2.7B
2 GB on disk
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2
Public
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.safetensors2 GB · 99%
How the weights are stored.
U322.7B · 100%
From the Hugging Face model README
Built with mlx-optiq, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon, no PyTorch and no cloud. All OptiQ quants · Docs · LFM2.5 family
An OptiQ mixed-precision quant of badtheorylabs/Macaw, an on-device Mac assistant built on LFM2.5-2.6B. 1.93 GB on disk, down from 5.2 GB at bf16.
Macaw is a tool-calling agent, so the quant is aimed at keeping tool calls well formed rather than at raw benchmark scores.
| Property | Value |
|---|---|
| Base | badtheorylabs/Macaw (LFM2.5-2.6B derivative) |
| Architecture | lfm2 — hybrid conv + full attention, 30 layers |
| Method | OptiQ mixed-precision, per-layer bit allocation reused from the base family |
| On disk | 1.93 GB (bf16: 5.2 GB) |
| Context | 128k |
Macaw keeps its base architecture, so which layers tolerate fewer bits is unchanged. The per-layer allocation comes from LFM2.5-2.6B-OptiQ-4bit rather than a fresh sensitivity sweep: 167 of 167 layers matched, 80 kept at 8-bit and 87 at 4-bit.
pip install mlx-optiq
optiq serve --model mlx-community/Macaw-OptiQ-4bit
That gives you an OpenAI and Anthropic compatible endpoint with mixed-precision KV cache, tool-call healing and prompt caching. The base model's recommended sampling ships in generation_config.json and optiq serve applies it without any flags.