Comprehensive side-by-side LLM comparison
Qwen2.5-VL 32B Instruct leads with 3.8% higher average benchmark score. Qwen2.5-VL 32B Instruct supports multimodal inputs. 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-VL-32B-Instruct is a 32-billion-parameter vision-language model from Alibaba, extending the Qwen2.5 architecture with multimodal capabilities for understanding images, documents, charts, and video frames alongside text. The model was designed for tasks requiring deep visual reasoning — such as document parsing, table extraction, and spatial understanding — with performance that made it a practical choice for document intelligence and visual data analysis workflows. As an open-weight model, it became a widely adopted foundation for fine-tuning domain-specific multimodal applications.
8 months newer
Qwen2 72B Instruct
Alibaba / Qwen
2024-06-07
Qwen2.5-VL 32B Instruct
Alibaba / Qwen
2025-03-01
Average performance across 1 common benchmarks
Qwen2 72B Instruct
Qwen2.5-VL 32B Instruct
Performance comparison across key benchmark categories
Qwen2 72B Instruct
Qwen2.5-VL 32B Instruct
Available providers and their performance metrics
Qwen2 72B Instruct
Qwen2.5-VL 32B Instruct
Qwen2 72B Instruct
Qwen2.5-VL 32B Instruct