Qwen 2.5
Alibaba's open-weight LLM family
5 billion to 72 billion parameters, along with specialized variants for coding and mathematics, designed for strong multilingual and general-purpose performance.
Definition
Qwen 2.5 is a family of open-weight large language models developed by Alibaba Cloud, released in multiple sizes ranging from about 0.5 billion to 72 billion parameters, along with specialized variants for coding and mathematics, designed for strong multilingual and general-purpose performance.
Overview
Qwen 2.5 is the third major generation in Alibaba's Qwen model series, trained on an expanded pretraining corpus reportedly covering trillions of tokens across dozens of languages, with particular strength in Chinese and English but broad multilingual coverage beyond that. The family spans a wide range of model sizes, letting developers pick a tradeoff between quality and deployment cost, from small models suitable for edge or mobile inference up to a 72-billion-parameter flagship competitive with other leading open models on many benchmarks. Alongside the general-purpose models, Alibaba released specialized Qwen 2.5 variants: Qwen2.5-Coder, tuned specifically for code generation and understanding across many programming languages, and Qwen2.5-Math, tuned for mathematical reasoning and problem solving. This specialization strategy reflects a broader industry trend of releasing both general foundation models and task-tuned derivatives from the same base architecture and training pipeline. Qwen 2.5 models are released under permissive open licenses (with some size tiers under Apache 2.0 and larger tiers under a Qwen-specific license), making them popular choices for self-hosted deployment, fine-tuning, and integration into custom applications where sending data to a third-party API is undesirable. The models support long context windows and function calling, and they are widely available through platforms like Hugging Face, Ollama, and various cloud inference providers, contributing to a large ecosystem of community fine-tunes and quantized versions.
Key Features
- Multiple model sizes from 0.5B to 72B parameters
- Broad multilingual training with particular strength in Chinese and English
- Specialized Qwen2.5-Coder and Qwen2.5-Math variants
- Open-weight release under permissive licenses for most size tiers
- Long context window support
- Function/tool calling support for agentic applications
- Widely available on Hugging Face, Ollama, and cloud inference platforms
- Large ecosystem of community fine-tunes and quantized versions