Comprehensive side-by-side LLM comparison
UI-TARS-72B-DPO supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Alibaba / Qwen
Qwen3-Coder-480B-A35B-Instruct, released by Alibaba's Qwen team on July 22, 2025, is a Mixture-of-Experts large language model with 480 billion total parameters and 35 billion active parameters per inference, specifically designed for agentic coding tasks. It features a 256K token native context window (extendable to 1M tokens with extrapolation) and demonstrated competitive performance on agentic coding, browser automation, and tool-use benchmarks. Qwen3-Coder-480B targets automated software engineering, multi-step code agents, and open-source coding deployments under the Apache 2.0 license.
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.
6 months newer
UI-TARS-72B-DPO
ByteDance
2025-01
Qwen3-Coder-480B
Alibaba / Qwen
2025-07-22
Context window and performance specifications
Available providers and their performance metrics
Qwen3-Coder-480B
OpenRouter
UI-TARS-72B-DPO
Qwen3-Coder-480B
UI-TARS-72B-DPO
Qwen3-Coder-480B
UI-TARS-72B-DPO