Qwen3.5 122B A10B Alternatives

This is a GGUF-quantized release of Qwen3-235B-A22B, a massive mixture-of-experts language model optimized for local execution. It supports advanced reasoning, tool calling, and follows a specific chat template. Provided by Unsloth, it enables efficient inference of one of the largest open models using tools like llama.cpp.

Qwen3-8B-GGUF is the GGUF-quantized format of Alibaba's Qwen3-8B model. This version enables efficient local inference on consumer hardware using tools like llama.cpp or Ollama. It retains strong language understanding and generation capabilities while supporting tool calling and structured prompting formats.

This is the GGUF quantized format of Alibaba's Qwen3-4B large language model. It enables efficient local inference using tools like llama.cpp or LM Studio. The model includes support for tool calling and follows a specific chat template for structured interactions.

Qwen3-14B-GGUF contains GGUF format files for the 14 billion parameter Qwen3 model, enabling efficient local execution using tools like llama.cpp. It supports advanced features such as tool calling and follows a specific chat template for multi-turn conversations. This allows developers to run a powerful open LLM on consumer hardware without relying on cloud APIs.

GGUF quantized versions of the Qwen3.5-2B model, optimized by Unsloth for fast local inference. Compatible with llama.cpp, Ollama, and other GGUF runtimes. Suitable for edge devices or low-memory environments while retaining strong language modeling performance.

This repository contains GGUF quantized files for the Qwen3.6-27B model. The quantization allows the large 27-billion-parameter model to run efficiently on consumer-grade hardware. It supports multimodal inputs (including vision) along with advanced features such as tool calling and structured conversation formats.

Qwen3.5-35B-A3B-GGUF is an open-source large language model designed for local inference and research. It enables developers and researchers to run text generation tasks efficiently on their own hardware with open weights.

Qwen3.5-27B-GGUF is an open-source large language model released in GGUF format for local inference and experimentation. It is suitable for AI researchers and developers who require access to model weights and the ability to run models on their own hardware.

Qwen3-30B-A3B-GGUF provides GGUF quantized weights for the Qwen3 30B-A3B model, enabling efficient local execution with tools like llama.cpp. It supports advanced features including tool calling and follows a specific chat template for multi-turn conversations. The model is intended for developers who want to run powerful language models offline.

This repository provides GGUF quantized weights for the 0.6 billion parameter Qwen3 model. It is optimized for use with Unsloth, supporting fast fine-tuning and inference. The model includes advanced features such as tool calling and is designed for users who want a lightweight yet powerful open LLM that runs locally.

Qwen3-4B-GGUF provides a quantized version of the Qwen3 4B parameter model in GGUF format, optimized for efficient inference and fine-tuning using Unsloth. It supports local execution on consumer hardware with features like chat templates and tool calling capabilities. Primarily used by developers and researchers looking to run or customize open-weight language models without relying on cloud APIs.

Qwen3.6-27B-GGUF is an open-source large language model distributed in GGUF format for local inference. It is designed for AI researchers and developers who require a powerful language model that can be run on local hardware for experimentation and development.

This repository provides GGUF quantized weights for the Qwen3.6-27B model, optimized for use with local inference engines such as LM Studio, llama.cpp, and similar tools. It enables running a powerful language model on standard consumer GPUs or CPUs.

Qwen3.5-35B-A3B-GGUF is an open-source large language model distributed by Unsloth on Hugging Face. It supports local inference, multiple quantizations, and is designed for AI researchers and developers seeking to run LLMs on their own hardware.

This repository provides GGUF quantized files for the Qwen3.6-35B model using an A3B (likely MoE or distilled) architecture. It is optimized for local inference with tools such as LM Studio. The model includes advanced tool-calling capabilities and a sophisticated chat template for complex interactions.

Qwen3.5-9B-GGUF is a community-provided collection of GGUF-quantized files for the Qwen3.5-9B language model. It enables efficient local execution using tools such as LM Studio, llama.cpp, or Ollama. The repository is targeted at developers and enthusiasts who want to run a capable open-source LLM on their own machines without relying on cloud APIs.

Qwen3.5-4B is a compact multimodal model from the Qwen series, optimized by Unsloth for faster inference. It supports both text and vision inputs with a custom chat template. The model is distributed on Hugging Face and can be used with standard transformers or Unsloth libraries.

Qwen3.6-35B-A3B-GGUF is an open-source, quantized large language model distributed in GGUF format for local inference and research. It enables developers and researchers to run advanced language models on their own hardware, supporting experimentation and customization. The model is freely available for use and modification.

Qwen3.5-0.8B-GGUF is an open-source foundation language model distributed in GGUF format for local inference. It enables developers and researchers to run advanced text generation tasks on their own hardware without relying on cloud APIs.

zlaabsi/Qwen3.6-27B-OTQ-GGUF provides GGUF quantized weights of the Qwen3.6 27B model, enabling efficient local inference with tools like llama.cpp. The model supports multimodal inputs and is suitable for developers who want to run powerful language and vision models on their own machines without cloud dependency.

Qwen3.6-27B-MTP-GGUF is an open-source large language model distributed in GGUF format for efficient local inference. It enables developers to run advanced text generation tasks on their own hardware without relying on cloud services.

Qwen3.6-27B-NVFP4 is an open-source large language model supporting both text and vision modalities. It can be deployed locally or in the cloud, making it suitable for AI researchers and developers who need flexible, high-capacity models for advanced NLP and computer vision tasks.

This is a GGUF quantized version of the Qwen3-30B-A3B-Instruct model optimized for local use. It includes support for tool calling and follows an instruction-tuned format. The model is distributed by Unsloth and is compatible with popular GGUF inference engines.

Qwen2.5-VL-7B-Instruct-GGUF is a repository on Hugging Face that supplies GGUF quantized files of the Qwen2.5-VL 7B vision-language model. It is intended for local inference of a multimodal model capable of processing both images and video alongside text. The repository is provided by unsloth. The files include variants such as Qwen2.5-VL-7B-Instruct-BF16.gguf and Qwen2.5-VL-7B-Instruct-IQ4_NL.gguf. A chat template is defined that handles messages containing text, image, or video content by inserting specific vision and image or video pad tokens. The template supports counting multiple images or videos in a conversation and adds optional identifiers such as "Picture 1:" or "Video 1:" before the visual tokens. It uses special tokens including vision_start, vision_end, image_pad, video_pad, im_start, and im_end. The total file size across the GGUF files is 15237851776 bytes. These quantized models are distributed for use with compatible inference engines that accept the GGUF format. The repository forms part of the broader collection of foundation models available on the platform. No pricing, licensing terms, or additional deployment details beyond the GGUF files and chat template are stated.

Qwen3.5-9B is a mid-sized multimodal model supporting both text and vision inputs. Optimized by Unsloth for faster training and inference, it includes advanced chat templates for vision and video content. The model is distributed via Hugging Face for local or cloud deployment.

This is an optimized version of the Qwen3-1.7B language model provided by Unsloth. It includes support for advanced chat templates, tool calling, and function calling capabilities. The model is designed for efficient training and inference, allowing developers to fine-tune large models on consumer hardware with significantly reduced memory requirements compared to standard implementations.

Qwen_Qwen3.6-27B-GGUF contains GGUF quantized files for the Qwen3.6-27B model. It supports text and vision inputs and is compatible with llama.cpp and other GGUF runtimes. Various quantization levels are provided to suit different hardware capabilities.

This is a GGUF-quantized version of the Qwen3.6-35B-A3B model, optimized for efficient local inference using tools like llama.cpp. It supports multimodal inputs and is designed for developers who want to run powerful language models on standard hardware without relying on cloud APIs.