Comprehensive side-by-side LLM comparison
Qwen2.5 14B Instruct leads with 1.8% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
Alibaba / Qwen
Qwen2-72B-Instruct is a 72-billion-parameter language model released by Alibaba's Qwen team in June 2024, serving as the flagship of the Qwen2 generation and representing a major step in open-weight multilingual modeling. Trained on data spanning 30+ languages with strong coverage of code and structured reasoning, the model was among the first openly released 70B-class models to demonstrate competitive performance across diverse benchmarks. It established the foundation architecture and training methodology that the Qwen2.5 series would later extend.
Alibaba / Qwen
Qwen2.5-14B-Instruct is a 14-billion-parameter language model from Alibaba released in September 2024 within the Qwen2.5 family, occupying the mid-tier of the series between efficiency-focused small models and the high-capability 72B flagship. Trained on 18 trillion tokens with emphasis on instruction alignment, code understanding, and multilingual reasoning, it offers a strong performance-to-compute ratio for developers who need more capability than 7B but cannot serve 32B or larger models. The model supports 128K context windows and structured output generation out of the box.
3 months newer
Qwen2 72B Instruct
Alibaba / Qwen
2024-06-07
Qwen2.5 14B Instruct
Alibaba / Qwen
2024-09-19
Average performance across 1 common benchmarks
Qwen2 72B Instruct
Qwen2.5 14B Instruct
Performance comparison across key benchmark categories
Qwen2 72B Instruct
Qwen2.5 14B Instruct
Available providers and their performance metrics
Qwen2 72B Instruct
Qwen2.5 14B Instruct
Qwen2 72B Instruct
Qwen2.5 14B Instruct