QwQ 32B Alternatives

Qwen/Qwen3-32B is an open-source large language model designed for advanced natural language understanding and generation tasks. It supports instruction following and multilingual capabilities, making it suitable for developers and researchers building AI-powered applications.

Qwen3-32B-AWQ is an open-source large language model designed for advanced text generation and tool calling. It is suitable for AI developers and researchers seeking a powerful LLM for integration into applications or research workflows.

Qwen2.5-3B is part of Alibaba's Qwen2.5 family of open foundation models. The 3B variant offers a balance of performance and efficiency, supporting chat, reasoning, coding, and tool-calling use cases. It includes an advanced chat template with tool integration and is distributed as open weights on Hugging Face for flexible deployment.

Qwen2.5-VL-32B-Instruct-AWQ is a quantized version of Alibaba's large vision-language model. It accepts image, video, and text inputs and generates text outputs for tasks such as visual question answering, captioning, and document understanding. The AWQ quantization enables more efficient deployment while maintaining strong multimodal performance.

Qwen3-32B-NVFP4 is an FP4 quantized version of the Qwen3-32B model created by NVIDIA. It includes support for tool calling and is optimized for high-performance inference on NVIDIA GPUs. The model is distributed on Hugging Face for developers seeking state-of-the-art performance with reduced memory and compute requirements.

Qwen3.5-27B is a 27B parameter open-source large language model for advanced text generation and conversational AI. It is designed for AI researchers and developers building sophisticated NLP applications, with support for CLI, API, and Docker deployment.

Qwen3-8B-Base is the foundational 8B parameter model of the Qwen3 family. It features an enhanced architecture supporting long contexts, multilingual performance, and native tool-calling abilities. It is designed as a base for further fine-tuning and is compatible with the Transformers library.

Qwen2.5-14B is part of the Qwen2.5 series of large language models from Alibaba's Qwen team. It features strong performance on reasoning, coding, and multilingual tasks. The model includes a chat template supporting tool/function calling and is provided with full weights on Hugging Face for local inference or fine-tuning.

Qwen3.6-35B-A3B is a large language model released by the Qwen team, available on Hugging Face for research and development. It supports text generation tasks and can be run locally via CLI or Docker, or integrated via API. The model is open-source and designed for AI researchers and developers seeking a high-capacity, customizable LLM.

A 4 billion parameter version of the Qwen3 large language model in FP8 precision. It supports instruction following, tool calling, and general text generation. The model is hosted on Hugging Face and can be used locally or via inference providers.

Qwen3-30B-A3B-Base is a Mixture-of-Experts base model released by Qwen. It is distributed as open weights on Hugging Face and supports advanced prompting, tool use, and efficient inference through quantization. It can be installed via pip or Docker and deployed on local hardware or cloud platforms.

Qwen2-7B is the 7 billion parameter version of the Qwen2 series of large language models developed by Alibaba. It supports conversational chat, instruction following, and tool use. The model is distributed as open weights on Hugging Face and can be run locally with Transformers or inference engines. It is suitable for developers building AI applications that require strong language understanding and generation capabilities.

Qwen3.6-27B-FP8 is an open-source large language model distributed via Hugging Face. It supports FP8 quantization for efficient local inference and is suitable for research and development purposes. The model is accessible to AI researchers and developers.

Qwen3-14B-AWQ is a 14-billion parameter open-source language model designed for advanced text generation and understanding. It supports quantized weights for efficient inference and can be integrated into various NLP applications by developers and researchers.

Qwen3-14B-FP8 is a quantized version of Alibaba's Qwen3 14B model optimized for efficient inference. It supports advanced features such as tool calling and follows an instruction-tuned chat template. The model is distributed on Hugging Face for developers who need high-performance open language models that can run on consumer or enterprise hardware.

Qwen3-32B-FP8 is an FP8-quantized version of Alibaba's Qwen3 32B large language model. It supports advanced capabilities including tool calling, long-context understanding, and multilingual performance while significantly reducing VRAM usage compared to the original. The model is designed for local and self-hosted inference by developers building AI applications.

Qwen3.5-2B is an open-source large language model designed for text generation and understanding. It supports a wide range of NLP tasks and is suitable for developers and researchers seeking advanced language capabilities in their applications.

Qwen2.5-Coder-32B-Instruct-AWQ is an open-source large language model hosted on Hugging Face. It belongs to the Qwen2.5-Coder series and is provided in an AWQ quantized format for efficient inference. The model includes a specific chat template that defines its instruction-following behavior. When a conversation begins without a system message it defaults to the prompt "You are Qwen, created by Alibaba Cloud. You are a helpful assistant." The template also supports tool calling through a structured XML-based format that supplies function signatures and expects JSON arguments wrapped in tool_call tags. It is delivered as a downloadable model repository on the Hugging Face platform. The presence of the AWQ variant indicates it is intended for deployment scenarios that benefit from reduced memory usage and faster execution on compatible hardware. The page title and repository path confirm the exact identifier Qwen/Qwen2.5-Coder-32B-Instruct-AWQ. No pricing information is stated because the model is distributed through the open Hugging Face ecosystem. The surrounding site context emphasizes open source and open science, aligning with free access to the weights and associated template.

Qwen3.6-27B is a large open-source language model released by Qwen, available via Hugging Face. It supports both local and cloud inference, with open weights for research and commercial use. Developers can install it using pip or Docker and integrate it into their AI workflows.

This is an AWQ-quantized 27B parameter version of Alibaba's Qwen3.5 language model. It supports text generation, tool use, and multimodal inputs while requiring significantly less memory than the original. The model is distributed via Hugging Face for use with popular inference frameworks.

Qwen1.5-7B is the 7 billion parameter version of Alibaba's Qwen1.5 series of large language models. It supports the ChatML prompt format and is optimized for a wide range of natural language tasks. The model is available through the Hugging Face Transformers library and can be run locally or via Docker.

Qwen3.5-35B-A3B is an open-source large language model supporting both text and multimodal inputs. It is designed for advanced AI applications, including chatbots and multimodal assistants, and is suitable for developers and researchers in AI.

This is a 4-bit quantized (bitsandbytes) version of Alibaba's Qwen3-VL-32B-Instruct model, optimized by Unsloth for efficient inference. It supports vision-language tasks including image understanding, visual question answering, and document analysis. The model uses a chat template optimized for tool use and can be run locally or in notebooks.

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.

Qwen3.5-9B is an open-source large language model from the Qwen family, designed for text generation and conversational AI. It is intended for developers and researchers building advanced NLP and AI applications.

Qwen3.5-4B-Base is the foundational 4 billion parameter model from Alibaba's Qwen 3.5 series. It serves as a strong base for further fine-tuning or continued pre-training. The model supports long context lengths and strong multilingual performance. It is distributed openly on Hugging Face and can be used with the Transformers library or other compatible inference frameworks.

Qwen3-14B is an open-source large language model designed for advanced text generation and understanding. It supports instruction following, multilingual capabilities, and is suitable for AI developers and researchers seeking a flexible, locally deployable LLM.

Qwen/Qwen3.6-35B-A3B-FP8 is an open-source large language model designed for advanced text generation and understanding. It supports instruction following and multilingual capabilities, making it suitable for developers and researchers building AI-powered solutions.

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.

Qwen3-8B is an open-source large language model designed for text generation and conversational AI tasks. It supports fine-tuning and can be deployed locally or via API, making it suitable for machine learning engineers building advanced NLP applications.

Qwen2-1.5B is part of the Qwen2 series of large language models developed by Alibaba. With 1.5 billion parameters, it offers a balance between performance and efficiency for text generation, instruction following, and conversational tasks. It supports a chat template for structured dialogue and is widely used as a base for further fine-tuning or direct inference.