Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
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.
ByteDance
UI-TARS-72B-DPO, released by ByteDance in early 2025, is a 72 billion parameter multimodal large language model from the UI-TARS family, built on Qwen-2-VL and fine-tuned for automated GUI interaction and computer control. It features native understanding of screenshots, UI elements, and web interfaces, achieving strong results across GUI benchmarks for perception, grounding, and agentic control. UI-TARS-72B-DPO targets computer-use agents, web automation, and applications requiring robust visual UI reasoning.
1 month newer
UI-TARS-72B-DPO
ByteDance
2025-01
Qwen2.5-VL 32B Instruct
Alibaba / Qwen
2025-03-01
Available providers and their performance metrics
Qwen2.5-VL 32B Instruct
UI-TARS-72B-DPO
Qwen2.5-VL 32B Instruct
UI-TARS-72B-DPO