Qwen3 Coder 30B A3B Instruct Alternatives

Qwen3-Coder-30B-A3B-Instruct-AWQ is a quantized version of Alibaba's Qwen3 coding model optimized with AWQ for reduced memory usage and faster inference. It supports code generation, completion, and instruction-following tasks. The model is distributed on Hugging Face and can be used with Transformers, vLLM, or other inference engines supporting GGUF/AWQ formats.

A quantized variant of the Qwen3-Coder model using AWQ 4-bit compression. It is designed for local inference of code generation and programming assistance tasks while significantly lowering VRAM usage compared to the original model. The model includes a chat template suitable for instruction following and tool use.

Qwen/Qwen3-Coder-30B-A3B-Instruct is an instruction-tuned large language model optimized for code generation and programming tasks. It is open source and suitable for developers and researchers seeking advanced AI coding assistants or tools.

Qwen3-Coder-30B-A3B-Instruct-FP8 is an open-source large language model designed for code generation and instruction following. It enables developers to automate programming tasks and integrate advanced code understanding into their workflows. The model is available for local or cloud deployment and supports a variety of programming languages.

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.

Qwen2.5-Coder-3B-Instruct is a 3 billion parameter instruction-tuned language model hosted on Hugging Face. It forms part of the Qwen2.5 series and is specialized for coding tasks. The model follows a system prompt that identifies it as Qwen, created by Alibaba Cloud, and positions it as a helpful assistant capable of using external tools when needed. The provided template defines a chat format that includes support for function calling. When tools are supplied, the model receives their signatures inside XML-style tags and is instructed to return calls in a structured JSON format wrapped in tool_call tags. This mechanism enables the model to invoke functions to assist with user queries. The template also handles both system and user messages with specific start and end tokens. It is delivered as an open model on the Hugging Face platform, where users can access the repository for download and inference. The page is part of Hugging Face's collection of models, datasets, and related resources aimed at advancing artificial intelligence through open source and open science.

Qwen2.5-Coder-7B-Instruct-AWQ is a 7 billion parameter model from Alibaba's Qwen2.5 series, specialized for coding tasks and instruction following. The AWQ-quantized version enables efficient deployment while retaining strong performance on code completion, debugging, and agentic programming workflows. It is distributed openly on Hugging Face.

Qwen2.5-Coder-7B-Instruct-AWQ is a quantized version of Alibaba's Qwen2.5 Coder model optimized for code generation and software development tasks. It supports instruction following and tool use. The model is intended for developers seeking a capable coding assistant that can run locally or in private environments.

A massive Mixture-of-Experts coding model from the Qwen team, quantized to FP8. It excels at code generation, debugging, and following complex instructions. The model includes advanced tool-calling capabilities and is designed for software developers and AI coding agents.

Qwen2.5-Coder-14B-Instruct is a large language model hosted on Hugging Face for code-related tasks. It forms part of the Qwen2.5 series developed by Alibaba Cloud and follows a specific chat template that defines its behavior as a helpful assistant created by the company. The model implements a structured prompt format for handling conversations and tool use. When a system message is present it incorporates that content directly; otherwise it defaults to an internal system prompt identifying itself as Qwen from Alibaba Cloud. It supports function calling by accepting tool definitions inside XML-style tags and requires responses for tool invocations to appear inside designated XML tags containing JSON objects with function name and arguments. This format enables the model to process user queries that may involve external function calls. The model is delivered as an open model repository on the Hugging Face platform. Users can access it through the standard Hugging Face ecosystem for download, inference, or integration into applications. No pricing information is stated for the model itself.

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-Coder-Next-AWQ-4bit is a quantized variant of the Qwen3 coding model optimized with AWQ for efficient local inference. It supports advanced chat templates and tool calling, making it suitable for code generation, completion, and software development assistance. The model is distributed on Hugging Face for developers seeking high-performance coding LLMs on consumer GPUs.

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.

This is an AWQ 4-bit quantized version of the Qwen3-VL-30B-A3B-Instruct multimodal model. It combines vision and language capabilities for tasks involving images and text, supporting tool use and structured output. The quantization enables efficient inference on more accessible hardware while preserving most of the original model's performance.

Qwen2.5-Coder-7B-Instruct is an instruction-tuned language model hosted on Hugging Face. It forms part of the Qwen series developed by Alibaba Cloud and follows a default system prompt that identifies it as Qwen, a helpful assistant created by Alibaba Cloud. The model includes a chat template that supports system, user, and assistant messages. It also defines a specific format for tool use, allowing the model to call one or more functions when needed. Function signatures are supplied inside XML-style tools tags, and each call must be returned as a JSON object wrapped in tool_call tags. This structure enables the model to integrate external functions during interaction. The model is delivered as a downloadable asset on the Hugging Face platform, where it can be loaded for local or hosted inference. No pricing, licensing terms, or additional supported platforms appear in the provided page content. The entry is based solely on the model card and template details shown there.

Qwen2.5-Coder-0.5B-Instruct is a compact 0.5 billion parameter model from the Qwen series, specialized for coding tasks. It supports code generation, completion, and understanding while being small enough to run efficiently on local devices. It is designed for developers seeking a lightweight coding assistant that can be self-hosted or integrated into IDEs.

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.

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.

Qwen3-30B-A3B-Instruct-2507 is a large-scale, instruction-tuned language model designed for advanced text generation and comprehension. It is intended for developers and researchers seeking high-quality, open-source LLMs for various NLP applications.

Qwen2.5-Coder-7B-Instruct-GPTQ-Int4 is a quantized 7B parameter model hosted on Hugging Face. It belongs to the class of instruction-tuned large language models specialized for coding tasks. The model includes a specific chat template that defines its behavior for conversations. When the first message is a system prompt it uses that content; otherwise it defaults to the instruction that it is Qwen created by Alibaba Cloud and a helpful assistant. The template further supports tool calling by providing function signatures inside XML tags and instructing the model to return calls in a structured JSON format wrapped in tool_call tags. This enables the model to invoke external functions during interaction. It is delivered as a downloadable model repository on the Hugging Face platform. The GPTQ-Int4 designation indicates the model has been quantized to 4-bit integer precision using the GPTQ method, allowing it to run with reduced memory requirements compared to the full-precision version. The page provides the exact prompt format used by the model for consistent behavior across deployments. No pricing information appears because the artifact is freely downloadable.

This repository hosts GGUF quantized files for Qwen2.5-Coder-14B-Instruct, a specialized 14-billion parameter model for code generation and software development tasks. It supports advanced features such as tool calling and follows a chat template optimized for coding assistance. Ideal for local development environments and offline coding agents.

A GGUF quantized version of Alibaba's Qwen2.5-Coder 14B Instruct model. It is optimized for code generation, completion, and reasoning tasks. The GGUF format allows efficient local execution using tools such as llama.cpp, LM Studio, and Ollama.

Qwen2.5-Coder-1.5B-Instruct-GGUF contains quantized GGUF files for the 1.5 billion parameter instruction-tuned coding model from the Qwen2.5 family. Optimized for local execution, it supports code generation, debugging, and tool calling while maintaining strong performance for its size. Suitable for developers needing on-device or offline coding assistance.