Qwen2.5 Coder 7B Instruct Alternatives

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-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-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-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-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-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-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-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.

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.

Qwen2.5-32B-Instruct-GPTQ-Int4 is a quantized variant of the Qwen2.5 32B instruction-tuned language model hosted on Hugging Face. It is provided as a GPTQ-Int4 model file intended for inference on compatible hardware. The model follows a system prompt that identifies it as Qwen created by Alibaba Cloud and positions it as a helpful assistant. The page supplies a chat template that defines how the model processes messages. When a system message is present it uses that content; otherwise it defaults to stating that the model is Qwen created by Alibaba Cloud and is a helpful assistant. The template also includes explicit support for tool use. It instructs the model that it may call one or more functions to assist with a user query, supplies function signatures inside XML-style tools tags, and requires each function call to be returned as a JSON object wrapped in tool_call XML tags. This structure enables the model to handle tool calling and function calling formats during generation. The model is distributed through the Hugging Face repository at Qwen/Qwen2.5-32B-Instruct-GPTQ-Int4. It belongs to the class of foundation models made available for download and local or hosted inference.

Qwen2.5-32B-Instruct-GPTQ-Int8 is an INT8-quantized version of Alibaba's Qwen2.5 32B Instruct model. It supports advanced features including tool calling and follows a detailed chat template. The model is designed for efficient inference while retaining strong reasoning and instruction-following capabilities.

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.

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.

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.

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.

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-7B-Instruct-bnb-4bit is a quantized language model hosted on Hugging Face. It is the 4-bit version of the Qwen2.5-Coder-7B-Instruct model prepared by Unsloth and distributed for inference use. The model follows a specific chat template that begins with a system prompt identifying it as Qwen created by Alibaba Cloud and designates it as a helpful assistant. The template includes support for tool calling through an XML-based format that supplies function signatures inside tools tags and expects responses inside tool_call tags containing JSON with name and arguments fields. This structure enables the model to process messages and invoke external functions when required. It is delivered as a repository on the Hugging Face platform under the identifier unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit. Users obtain the model files through the standard Hugging Face ecosystem for loading with compatible inference libraries. The page belongs to the collection of open models that advance artificial intelligence through open source and open science. No pricing, licensing terms, or additional capabilities beyond the listed prompt format appear in the repository metadata.

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.

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.

This repository contains GGUF quantized versions of Alibaba's Qwen2.5-Coder-14B-Instruct model, optimized for use with LM Studio and other local LLM tools. It supports code generation, reasoning, and general instruction following with multiple quantization levels for different hardware.

Qwen2.5-7B-Instruct-GGUF provides quantized GGUF files for the 7B parameter instruction-tuned version of Alibaba's Qwen2.5 model. It supports advanced features such as tool calling and is optimized for local inference using engines like llama.cpp. The model serves as a helpful assistant and can be integrated into applications via the Transformers library or GGUF-compatible runtimes.

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.

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.

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.

Qwen2.5-3B-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.