Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. 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
Qwen2.5-7B-Instruct is a 7-billion-parameter open-weight language model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens with improved code, math, and multilingual coverage. The model delivers significantly stronger instruction-following, structured output generation, and long-context handling compared to its predecessor, supporting 128K context windows in a compact form factor. It became widely adopted as a foundation for fine-tuning, RAG pipelines, and on-device deployment due to its balance of capability and efficiency.
3 months newer
Qwen2 72B Instruct
Alibaba / Qwen
2024-06-07
Qwen2.5 7B Instruct
Alibaba / Qwen
2024-09-19
Average performance across 1 common benchmarks
Qwen2 72B Instruct
Qwen2.5 7B Instruct
Performance comparison across key benchmark categories
Qwen2 72B Instruct
Qwen2.5 7B Instruct
Available providers and their performance metrics
Qwen2 72B Instruct
Qwen2.5 7B Instruct
Qwen2 72B Instruct
Qwen2.5 7B Instruct