# Large Language Model

This is a 4-bit quantized version converted from the Qwen3-30B model, suitable for text generation tasks on the MLX framework.

This model is an MLX format version converted from deepseek-ai/deepseek-r1-0528-Qwen3-8B, suitable for local inference on Apple devices.

FairyR1-32B is a large language model with 32B parameters, developed by PKU-DS-LAB, focusing on text generation tasks.

Qwen3-32B-8bit is an 8-bit quantized version of the Qwen3-32B model, designed for text generation tasks and released by mlx-community.

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

Qwen2.5-Coder-7B-Instruct is a 7B-parameter code generation model based on the Qwen2.5 architecture, specializing in instruction fine-tuning, suitable for code generation and programming assistance tasks.

This is a mixed 3-6bit quantized version converted from the Qwen/Qwen3-235B-A22B model, optimized for efficient inference on the Apple MLX framework.

A quantized version of the Qwen2.5-VL-72B-Instruct multimodal large language model, supporting image-text-to-text tasks, suitable for various quantization levels from high precision to low memory requirements.

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

This is a 4-bit quantized version based on the Qwen3-30B-A3B model, created through custom DWQ quantization technology distilled from 6-bit to 4-bit, suitable for text generation tasks.

Qwen3 30B A3B is a large language model that has undergone 8-bit quantization using the GPTQ method, suitable for efficient inference scenarios.

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

This model is converted from Qwen/Qwen3-30B-A3B to the MLX format, supporting 8-bit quantization and suitable for text generation tasks.

Qwen3-30B-A3B-MLX-8bit is an 8-bit quantized version converted from Qwen/Qwen3-30B-A3B, optimized for the MLX framework and suitable for text generation tasks.

Qwen3-8B-bf16 is an MLX format model converted from Qwen/Qwen3-8B, supporting text generation tasks.

Qwen3-30B-A3B-8bit is an MLX format conversion version of the Qwen/Qwen3-30B-A3B model, supporting efficient operation on Apple chips.

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.

This model is a 4-bit quantized version of Qwen3-32B in MLX format, optimized for efficient operation on Apple Silicon devices.

GLM-4-32B-0414-abliterated is a large-scale language model based on the GLM architecture, with a parameter scale of 32B, suitable for text generation tasks.

This model is an 8-bit quantized MLX format conversion from THUDM/GLM-4-32B-0414, supporting Chinese and English text generation tasks.

GLM-4-32B-0414 is a large-scale language model developed by the THUDM team, based on the GLM architecture, suitable for various text generation tasks.

FP8 quantized version of Qwen2.5-VL-72B-Instruct, supporting vision-text input and text output, optimized and released by Neural Magic.

This model is a multimodal vision-language model converted from Qwen2.5-VL-7B-Instruct, supporting 8-bit quantization and suitable for visual question-answering tasks.

Gemma 3 27B IT QAT 4bit is an MLX-format model converted from Google's original model, supporting image-to-text tasks.

GLM-4-32B-0414 is a large-scale language model developed by THUDM, with 32 billion parameters, suitable for various text generation tasks.

VoRA is a vision-language model based on 7B parameters, focusing on image-text-to-text conversion tasks.

VoRA is a vision-language model based on 7B parameters, capable of processing image and text inputs to generate text outputs.

OpenHands LM 32B v0.1 is a 32B-parameter open-source large language model dedicated to the free dissemination of knowledge.

DeepSeek-V3-0324 is a powerful foundational model focused on text generation tasks, designed to deliver high-quality text generation capabilities.

VideoLLaMA2.1-7B-AV is a multimodal large language model focused on audio-visual question answering tasks, capable of processing both video and audio inputs to provide high-quality question answering and description generation.

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.

An 8-billion-parameter model featuring the innovative SuperBPE tokenizer, combining subword and super tokens, achieving 30% higher inference efficiency than traditional BPE models.

Mistral Small 3.1 Instruct 24B is a large language model based on instruction fine-tuning, focusing on text generation tasks.

A large language model fine-tuned on the codeforces-cots dataset based on google/gemma-3-12b-it

Gemma 3 12B is a large language model that provides a quantized version in GGUF format, suitable for local deployment and use.

INT8 quantized version of QWQ-32B, optimized by reducing the bit-width of weights and activations

A text-only version converted from google/gemma-3-12b-it, with visual components removed, focusing on text generation tasks

Gemma-3-12b-it is a large language model developed by Google, based on the transformer architecture, focusing on text generation tasks.

This is an MLX-converted version of the Google Gemma 3 27B IT model, supporting image-text-to-text tasks.

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