# 4-bit quantization

DiffuCoder-7B-cpGRPO-4bit is a 4-bit quantized version converted from the Apple DiffuCoder-7B-cpGRPO model, optimized for the MLX framework.

The 4-bit quantization version of Tencent Hunyuan A13B large language model, suitable for instruction following tasks

A Turkish language educational Q&A chatbot fine-tuned based on the Meta LLaMA 3.1 8B large language model, optimized specifically for Turkish language education scenarios.

This is a 4-bit quantized version converted from the Qwen3-235B-A22B-8bit model, optimized for the MLX framework and suitable for text generation tasks.

This is a 4-bit quantized model of Qwen3-30B-A3B-abliterated, with a parameter scale equivalent to 8B, suitable for text generation tasks.

This model is a 4-bit quantized version converted from DeepSeek-R1-0528-Qwen3-8B, optimized for the MLX framework and suitable for text generation tasks.

A large language model developed by DeepSeek AI, optimized with 4-bit quantization, suitable for Apple chip devices.

DeepSeek-R1-0528-4bit is a 4-bit quantized model converted from DeepSeek-R1-0528, optimized for the MLX framework.

This is a 4-bit quantized language model in MLX format, suitable for text generation tasks.

MedGemma-4B-IT-4bit is a vision-language model specifically designed for the medical field, supporting image and text processing, and suitable for tasks such as medical image analysis.

Qwen3-235B-A22B-4bit-DWQ is a 4-bit quantized version converted from the Qwen3-235B-A22B-8bit model, suitable for text generation tasks.

This model is a 4-bit DWQ quantized version of Qwen3-4B, converted to the MLX format for easy text generation using the mlx library.

This is a 4-bit quantized model converted from Qwen/Qwen3-30B-A3B to MLX format, suitable for text generation tasks.

Qwen3-30B-A3B-4bit-DWQ-0508 is a 4-bit quantized model converted from Qwen/Qwen3-30B-A3B to MLX format, suitable for text generation tasks.

An MNN model exported from Qwen3-30B-A3B, featuring 4-bit quantization for efficient inference.

Qwen3-8B-4bit-DWQ is a 4-bit quantized version of Qwen/Qwen3-8B converted to the MLX format, optimized for efficient operation on Apple devices.

This is a 4-bit quantized version in MLX format converted from the Microsoft Phi-4-mini-reasoning model, suitable for text generation tasks.

4-bit quantized version based on Qwen3-1.7B, a lightweight large language model optimized for the MLX framework

Qwen3-8B-4bit-AWQ is a 4-bit AWQ quantized version converted from Qwen/Qwen3-8B, suitable for text generation tasks in the MLX framework.

This model is a 4-bit quantized version of Qwen/Qwen3-235B-A22B converted to MLX format, suitable for text generation tasks.

This is the 4-bit quantized version of the Qwen/Qwen3-8B model, converted to the MLX framework format, suitable for efficient inference on Apple silicon devices.

Qwen3-30B-A3B-4bit is a 4-bit quantized version converted from Qwen/Qwen3-30B-A3B, suitable for efficient text generation tasks under the MLX framework.

Qwen3-4B-4bit is a 4-bit quantized version converted from Qwen/Qwen3-4B to the MLX format, designed for efficient operation on Apple chips.

Qwen3-1.7B-4bit is a 4-bit quantized version of the Tongyi Qianwen 1.7B model, which has been converted to the MLX framework format for efficient operation on Apple Silicon devices.

Qwen3-14B-4bit is a 4-bit quantized version of the Qwen/Qwen3-14B model converted using mlx-lm, suitable for text generation tasks.

The 4-bit quantized version of the MNN model for Qwen3-4B, used for efficient text generation tasks

A 4-bit quantized version based on InternVL2_5-1B, suitable for text generation and chat scenarios.

This model is a 4-bit quantized version converted from THUDM/GLM-Z1-32B-0414, suitable for text generation tasks.

Dia-1.6B-4bit is a 4-bit quantized text-to-speech model based on the MLX format, converted from nari-labs/Dia-1.6B.

HiDream-I1 is an open-source image generation foundation model with 17 billion parameters, capable of producing industry-leading images in seconds.

HiDream-I1 is an open-source image generation foundation model with 17 billion parameters. The 4-bit quantized version can run on 16GB VRAM, enabling fast and high-quality image generation.

HiDream-I1 is an open-source image generation foundation model with 17 billion parameters, capable of producing industry-leading images in seconds.

A Persian-specific model fine-tuned based on the Gemma 3 architecture, utilizing QLoRA 4-bit quantization technology, suitable for running on ordinary hardware.

This is the 4-bit quantized version of the Qwen/QwQ-32B model, optimized using the BitsAndBytes library, suitable for text generation tasks in resource-constrained environments.

The 4-bit quantized version of Qwen/QwQ-32B, implemented using the BitsAndBytes library, suitable for text generation tasks in resource-constrained environments.

This is a statically quantized version of the mshojaei77/gemma-3-4b-persian-v0 model, specifically optimized for Persian text generation tasks.

Gemma 3 is an instruction-tuned large language model developed by Google. This repository provides its 27B parameter W4A16 quantized version, significantly reducing hardware requirements

A Persian-specific model based on the Gemma 3 architecture, utilizing QLoRA for 4-bit quantization, focused on Persian text generation and understanding

This is a 4-bit quantized version converted from the allenai/OLMo-2-0325-32B-Instruct model, optimized for the MLX framework and suitable for text generation tasks.

4-bit quantized version of QwQ-32B, optimized using Bitsandbytes technology, suitable for efficient inference in resource-constrained environments