Downloads · 30 days
347
52% of all-time downloads
mlx-community/Fara1.5-9B-OptiQ-4bit
Fara1.5-9B-OptiQ-4bit is a image-text-to-text model from mlx-community. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as mit.
Built with mlx-optiq, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon (no PyTorch, no cloud). Try the Lab · All OptiQ quants · Docs Supported loaders: mlx-optiq (text, vision, an…
Downloads · 30 days
347
52% of all-time downloads
All-time downloads
670
Public
Parameters
9B
8 GB on disk
Likes
3
Public
Click a slice to open those files.
.safetensors8 GB · 100%
How the weights are stored.
U329B · 95%
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, no cloud). Try the Lab · All OptiQ quants · Docs
Supported loaders: mlx-optiq (text, vision, and MTP) and stock mlx-lm (text). Other front-ends load MLX weights through their own stack, so support there depends on that stack rather than on these files.
An OptiQ mixed-precision MLX quant of microsoft/Fara1.5-9B, a Qwen3.5-based computer-use / web-agent vision-language model.
mlx-community/Qwen3.5-9B-OptiQ-4bit quant. Fara1.5 is a finetune of Qwen3.5-9B with identical architecture, so the OptiQ allocation matches the Qwen3.5 family exactly, with no separate sensitivity pass.optiq/optiq_vision.safetensors. The one repo loads text-only under stock mlx-lm and full image+text under OptiQ.pip install -U optiq
optiq serve --model mlx-community/Fara1.5-9B-OptiQ-4bit
Use the OpenAI-compatible endpoint at http://localhost:8000/v1. Send an image_url part for the computer-use / vision path.