Qwen2.5 Coder 32B Instruct Alternatives

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.

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-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-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.

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-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.

Qwen2.5-Coder-32B-Instruct-GGUF is a code-specialized instruction-tuned language model released in GGUF format on Hugging Face. It forms part of the Qwen2.5 series developed by Alibaba Cloud and is intended for local inference on compatible runtimes. The model includes a system prompt that identifies it as Qwen, created by Alibaba Cloud, and positions it as a helpful assistant. Its prompt template supports tool calling through a defined XML-based format that supplies function signatures inside tools tags and expects JSON-structured calls inside tool_call tags. This mechanism allows the model to invoke external functions when assisting with user queries. It is delivered as downloadable GGUF files hosted on the Hugging Face model repository. The GGUF format enables execution through local inference engines such as llama.cpp. No pricing information appears in the repository page, and the model is provided under the open terms typical of Hugging Face model uploads from the Qwen organization. The repository page supplies the chat template used by the model but does not list specific coding benchmarks, parameter counts, supported languages, or additional capabilities beyond the tool-calling structure shown in the prompt.

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.

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.

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.

stelterlab/Qwen3-Coder-30B-A3B-Instruct-AWQ is a quantized version of a large language model hosted on Hugging Face. It belongs to the class of coding-focused AI models and provides an AWQ-quantized instruct variant intended for local or self-hosted inference. The repository contains model weights, tokenizer configuration, and a chat template in Jinja format. The tokenizer uses specific pad, bos, and eos tokens along with an end-of-text token. The provided chat template supports structured rendering of item lists, conditional system messages, and tool definitions for multi-turn conversations. It is delivered as downloadable files on the Hugging Face platform. Users obtain the model through the standard repository interface for use with compatible inference frameworks that support AWQ quantization and the included configuration files. No pricing, licensing terms, or named maker beyond the repository owner are stated in the page content. The surrounding Hugging Face site promotes open source and open science but does not attach specific license details to this model card.

Qwen2.5-7B-Instruct-AWQ is an instruction-tuned language model hosted on Hugging Face. It is provided in AWQ quantized format for efficient deployment and forms one variant within the Qwen2.5 model family. The model follows a specific chat template that begins with a system prompt identifying it as Qwen, created by Alibaba Cloud, and positions it as a helpful assistant. When tools are supplied, the template instructs the model to call functions by emitting structured JSON objects wrapped in XML-style tool_call tags. It supports multi-turn conversation handling through a sequence of messages that can include an optional initial system role. Delivery occurs via the Hugging Face platform, where the repository makes the model weights available for download and integration into inference pipelines. The page includes example Jinja-based chat template code that developers can use to format inputs correctly for text generation tasks. No pricing, licensing terms, or additional platform support details appear in the repository excerpt.

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.

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.

Qwen2.5-32B-Instruct is an open-source large language model designed for instruction-following and conversational AI tasks. Developed by Alibaba Cloud, it supports text generation, multi-turn dialogue, and custom fine-tuning. It is suitable for AI researchers and developers seeking a powerful, adaptable LLM for various natural language processing applications.

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.

Qwen2.5-Coder-7B-Instruct-GGUF contains quantized GGUF files for Alibaba's Qwen2.5-Coder 7B Instruct model. Optimized for code generation and software development tasks, it includes advanced tool calling and function calling capabilities. The model can be run locally with llama.cpp or other GGUF-compatible engines.

Qwen2.5-14B-Instruct is an instruction-tuned language model hosted on Hugging Face. It forms part of the Qwen2.5 series and is distributed with open weights. The model is positioned within the class of foundation models and is made available for download and use from the repository Qwen/Qwen2.5-14B-Instruct. The provided page content includes a system prompt template that defines its default behavior. It identifies the model as Qwen, created by Alibaba Cloud, and instructs it to act as a helpful assistant. The template supports conversation handling with an optional initial system message. When tools are supplied, the prompt instructs the model to consider calling one or more functions by returning structured JSON objects wrapped in XML-style tags. This mechanism enables the model to receive tool signatures in a designated XML block and to format its calls accordingly. The page is hosted by Hugging Face, an organization focused on advancing artificial intelligence through open source and open science. The content consists primarily of template code for formatting messages and tool interactions rather than a full model card or feature list.

Qwen2.5-Coder-1.5B is a compact member of the Qwen2.5-Coder family optimized for programming tasks. It supports code generation, debugging, and tool use through its instruction-tuned capabilities and provided chat templates. Available for local or hosted inference via the Hugging Face ecosystem.

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.

Qwen2.5-14B-Instruct-AWQ is an open-source large language model designed for instruction following and conversational tasks. It provides downloadable weights and supports local inference, making it suitable for researchers and developers seeking customizable LLM solutions.

Qwen2.5-1.5B-Instruct is a 1.5 billion parameter instruction-tuned language model hosted on Hugging Face. It forms part of the Qwen2.5 series and is made available as an open model for text-based tasks. The model includes a specific chat template that defines how it processes conversation history. When the first message is a system prompt it incorporates that content directly; otherwise it defaults to the instruction "You are Qwen, created by Alibaba Cloud. You are a helpful assistant." The template further supports tool use by inserting function signatures inside XML-style <tools> tags and instructing the model to emit calls inside <tool_call> tags containing JSON objects with name and arguments fields. This structure enables the model to handle multi-turn dialogues that may involve external function invocation. It is delivered as a downloadable model repository on the Hugging Face platform, allowing integration into applications that support the Transformers library or compatible inference runtimes. The page presents the model under the organization's open-source efforts, consistent with Hugging Face's focus on open models and open science.

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.

Qwen2.5-3B-Instruct is a 3-billion-parameter instruction-tuned language model published on Hugging Face by the Qwen team. It forms part of the Qwen2.5 series of foundation models and is provided for download and local use. The model includes a chat template that defines its default system prompt as "You are Qwen, created by Alibaba Cloud. You are a helpful assistant." The template supports multi-turn conversations and supplies explicit formatting for tool use. When tools are supplied, the prompt instructs the model to call one or more functions by emitting structured XML blocks containing a JSON object with function name and arguments. This mechanism allows the model to request external assistance while following a defined XML-based call format. The model is distributed as open-source weights on the Hugging Face repository. No pricing, licensing terms, or usage restrictions are stated on the page. It is delivered as downloadable model files that can be loaded with standard Hugging Face libraries for inference on compatible hardware.

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.