---
title: Fara1.5-9B-OptiQ-4bit
canonical_url: "https://www.modelscope.cn/models/latentnode/Fara1.5-9B-OptiQ-4bit"
md_url: "https://www.modelscope.cn/models/latentnode/Fara1.5-9B-OptiQ-4bit.md"
repository: latentnode/Fara1.5-9B-OptiQ-4bit
chinese_name: Fara1.5-9B-OptiQ-4bit
last_updated: 2026-07-27
license: mit
pipeline_tag: image-text-to-text
tasks:
  - image-text-to-text
model_type:
  - qwen3_5
architectures:
  - Qwen3_5ForConditionalGeneration
base_model:
  - microsoft/Fara1.5-9B
base_model_relation: quantized
parameters: 2.4B
tensor_type:
  - BF16
  - U32
library_name:
  - mlx
  - safetensors
language:
  - en
downloads: 18
stars: 0
tags:
  - mlx
  - optiq
  - computer-use
  - web-agent
  - agent
---

# Fara1.5-9B-OptiQ-4bit

> Fara1.5-9B-OptiQ-4bit - latentnode 在 ModelScope 开源的模型。Fara1.5-9B-OptiQ-4bit

latentnode/Fara1.5-9B-OptiQ-4bit 是 ModelScope 魔搭社区上的 2.4B 参数image-text-to-text模型，采用 mit 许可，基于 microsoft/Fara1.5-9B 构建。

- **Repository**: latentnode/Fara1.5-9B-OptiQ-4bit
- **License**: mit
- **Tasks**: image-text-to-text
- **Parameters**: 2.4B
- **Base model**: microsoft/Fara1.5-9B
- **Tags**: mlx, optiq, computer-use, web-agent, agent
- **Downloads**: 18
- **Stars**: 0
- **Last updated**: 2026-07-27

Source: https://www.modelscope.cn/models/latentnode/Fara1.5-9B-OptiQ-4bit

---

# Fara1.5-9B-OptiQ-4bit

> **Built with [mlx-optiq](https://mlx-optiq.com)**, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon (no PyTorch, no cloud). [Try the Lab](https://mlx-optiq.com/docs/lab/) · [All OptiQ quants](https://mlx-optiq.com/models) · [Docs](https://mlx-optiq.com/docs/)
>
> **Supported loaders:** [mlx-optiq](https://mlx-optiq.com) (text, vision, and MTP) and stock [mlx-lm](https://github.com/ml-explore/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](https://mlx-optiq.com) mixed-precision MLX quant of [microsoft/Fara1.5-9B](https://huggingface.co/microsoft/Fara1.5-9B), a Qwen3.5-based computer-use / web-agent vision-language model.

- **Mixed 4/8-bit**, 5.21 bits per weight (7.5G on disk).
- The per-layer bit allocation is **transferred from the published `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.
- **Vision tower kept at bf16** in `optiq/optiq_vision.safetensors`. The one repo loads text-only under stock `mlx-lm` and full image+text under OptiQ.

## Running it

```bash
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.