Qwen3.6 35B A3B Alternatives

Qwen3.6-35B-A3B-MLX-8bit is a community-quantized version of Alibaba's Qwen model using 8-bit precision and optimized for Apple's MLX framework. It supports text and vision inputs and can run locally on compatible hardware. The model is provided on Hugging Face for developers building local AI applications or experimenting with large language models without heavy cloud dependency.

This is a community-quantized 8-bit version of Qwen3.6-35B (with A3B MoE architecture) prepared for the MLX framework on Apple devices. It enables high-performance local inference on Macs with reduced memory footprint while retaining strong reasoning capabilities. The model uses standard MLX conversion and loading patterns.

Qwen3.6-35B-A3B-CompQuant-MLX-3bit is an open-source, quantized large language model optimized for local inference. It features 3-bit compression and MLX compatibility, making it suitable for researchers and developers needing efficient LLMs.

Qwen3.5-397B-A17B-8bit is a quantized version of the Qwen3.5 large language model optimized for the MLX framework. It supports multimodal inputs including text and vision, with a provided chat template for conversational use. The model is hosted on Hugging Face for easy integration into local or cloud inference pipelines by developers building AI applications.

This is a 4.75-bit PrismaQuant version of a Qwen3.6 35B-A3B model optimized for use with the vLLM inference engine. It supports multimodal inputs including vision and includes custom chat templates for tool use. The model is distributed on Hugging Face for efficient local or server-based deployment.

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.

This is a 6-bit quantized MLX version of the Qwen3-VL-4B vision-language model, optimized for Apple Silicon devices. It allows local multimodal inference combining vision and language understanding. The model is targeted at developers who want to run capable vision-language models on Macs or other local hardware without cloud services.

Qwen3-VL-8B-Instruct-MLX-5bit is a quantized version of the Qwen3 vision-language model optimized for MLX on Apple silicon. It supports multimodal inputs including text, images, and tools, enabling local execution of complex vision-language tasks. The model is distributed on Hugging Face for use with Transformers, MLX, and local inference tools.

This is a 6-bit quantized version of Qwen3-Coder optimized for the MLX framework on Apple devices. It is distributed on Hugging Face for local inference and is targeted at developers who want to run state-of-the-art coding assistants offline.

This is a 4-bit quantized version of the Qwen3-VL 4B Instruct model, optimized for the MLX framework on Apple silicon. It supports multimodal inputs (text and images) and includes advanced tool-calling capabilities. The model is distributed by the LM Studio community for local inference on compatible hardware.

A 6-bit quantized version of the Qwen3-VL-8B-Instruct model optimized for the MLX framework. It supports vision-language tasks including image understanding and multimodal conversation. The quantization enables efficient local inference on Apple Silicon devices.

Qwen3.5-27B-MLX-4.5bit is an open-source, quantized large language model designed for efficient local text generation using the MLX framework. It supports local inference and is suitable for developers and researchers seeking to run LLMs on their own hardware.

Qwen3-VL-8B-Instruct-MLX-8bit is an 8-bit quantized version of the Qwen3-VL vision-language model, optimized for the MLX framework on Apple hardware. It supports multimodal instruction following and can process both text and images. The model is provided by the LM Studio community on Hugging Face for local deployment and experimentation.

This is a 4-bit quantized version of the Qwen3-VL-8B-Instruct vision-language model, optimized for the MLX framework on Apple Silicon. It supports multimodal inputs combining text and images and follows instruction-tuned behavior. The model is distributed on Hugging Face for local inference using MLX or related tools.

This is a 4-bit quantized MLX version of the Qwen3-Coder 30B (A3B Instruct) model. It is a coding-specialized large language model optimized for local execution on Apple hardware. The model excels at code generation, understanding, and related programming tasks while maintaining a manageable memory footprint.

Qwen3.6-35B-A3B-AWQ-4bit is a quantized version of a large language model, designed for efficient inference on local hardware. It is suitable for developers and researchers who need high-performance language models with reduced resource requirements.

A 6-bit quantized MLX version of the Qwen3-Coder 30B-A3B Instruct model, optimized for Apple Silicon devices. It supports code generation, instruction following, and tool use. Maintained by the LM Studio community for seamless local execution on Macs.

This is a 4B parameter quantized version of the Qwen3-VL vision-language model optimized for MLX. It supports multimodal inputs combining text and images and can be used for visual question answering, document understanding, and tool-calling tasks. The model is distributed on Hugging Face for local inference via libraries such as Transformers or MLX.

Qwen3-VL-4B-Instruct-MLX-8bit is an 8-bit quantized version of the Qwen3-VL 4B vision-language model optimized for the Apple MLX framework. It supports multimodal input (images + text), instruction following, and tool calling. The model is distributed via Hugging Face for local inference on Macs.

This is an 8-bit quantized version of the Qwen3-Coder-Next model prepared for the MLX framework on Apple devices. It is distributed on Hugging Face for local inference in coding and software development tasks.

A 5-bit quantized MLX version of the Qwen3-Coder 30B-A3B Instruct model, optimized for Apple Silicon devices. It supports code generation, instruction following, and tool use. Maintained by the LM Studio community for seamless local execution on Macs.

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.

This is a community-quantized version of a Qwen3 coding model using 4-bit precision and optimized for the MLX framework on Apple devices. It includes a specialized chat template for code-related tasks and can be used through standard Hugging Face loading mechanisms or LM Studio.

A 4-bit AWQ quantized checkpoint of the Qwen3.5-35B-A3B Mixture-of-Experts model. It supports multimodal inputs including images and video and is optimized for local execution using tools compatible with the GGUF or AWQ format. The model is intended for developers wanting high-performance local AI capabilities.

This is a specialized, quantized variant of the Qwen 3.6 27B model optimized for the vLLM inference engine on NVIDIA Blackwell GPUs. It supports multimodal inputs and is designed for high-performance local or server-based deployment.

This is a community-quantized 8-bit version of the Qwen3-Coder 30B (with 3B active parameters) model using the MLX framework. It is optimized for local execution on Apple silicon devices and includes a chat template suitable for coding assistance and instruction following. The model is hosted on Hugging Face for developers building local AI coding tools.

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.

Qwen3.6-35B-A3B-MLX-VQ-3.4bpw is an open-source large language model available on Hugging Face, designed for natural language processing tasks. It supports local inference and can be integrated via API or CLI for research and development purposes. The model is suitable for AI researchers and developers seeking customizable LLMs.

Qwen3.5-9B-NVFP4 is a quantized (NVFP4) version of Alibaba's Qwen3.5-9B large language model. It is optimized for reduced memory usage and faster inference while maintaining strong performance. The model supports multimodal inputs and can be run locally using standard Hugging Face tools.

A heavily quantized (4-bit AWQ) version of a Qwen 3.6 model with 35B+3B parameters and vision capabilities (VRAP). The 21.2GB model supports both text and image inputs. It is designed for local inference using GGUF-compatible tools or optimized runtimes.

A 4-bit quantized version of the Qwen3-ASR-0.6B model optimized for Apple's MLX framework. Supports speech recognition for English, Chinese, Japanese, Korean, French, German, Spanish and other languages. Designed for efficient on-device or local-server transcription tasks.