Comprehensive side-by-side LLM comparison
Qwen2.5 72B Instruct leads with 4.2% 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
Qwen2.5-72B-Instruct is the flagship of Alibaba's Qwen2.5 series, a 72-billion-parameter open-weight model released in September 2024 after training on 18 trillion tokens spanning code, mathematics, and multilingual text. It offers strong generalist performance across coding, instruction-following, and structured reasoning while remaining fully open-weight under Apache 2.0 — a combination that made it a widely referenced model in open-source evaluations and community benchmarking. The 128K context window and built-in structured output support made it a common choice for document analysis and multi-step agentic pipeline development.
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.
5 months newer
Qwen2.5 72B Instruct
Alibaba / Qwen
2024-09-19
Qwen2.5-VL 32B Instruct
Alibaba / Qwen
2025-03-01
Average performance across 1 common benchmarks
Qwen2.5 72B Instruct
Qwen2.5-VL 32B Instruct
Performance comparison across key benchmark categories
Qwen2.5 72B Instruct
Qwen2.5-VL 32B Instruct
Available providers and their performance metrics
Qwen2.5 72B Instruct
Qwen2.5-VL 32B Instruct
Qwen2.5 72B Instruct
Qwen2.5-VL 32B Instruct