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Comprehensive side-by-side LLM comparison
UI-TARS-72B-DPO supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
MiniMax
MiniMax M2.5 is a large language model from MiniMax extensively trained with reinforcement learning across hundreds of thousands of complex real-world environments. It targets agentic tool use, coding automation, and office productivity tasks, with strong results on software engineering and web browsing benchmarks. M2.5 represents the next generation of MiniMax's M-series models optimized for production agentic workloads.
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 year newer
UI-TARS-72B-DPO
ByteDance
2025-01
Minimax M 2.5
MiniMax
2026-02-13
Context window and performance specifications
Available providers and their performance metrics
Minimax M 2.5
MiniMax
UI-TARS-72B-DPO
Minimax M 2.5
UI-TARS-72B-DPO
Minimax M 2.5
UI-TARS-72B-DPO