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DeepSeek-R1 vs UI-TARS-2
Comprehensive side-by-side LLM comparison
UI-TARS-2 supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning under an open MIT license.
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ByteDance
UI-TARS-2, released by ByteDance in September 2025, is a major generational upgrade of the UI-TARS family of GUI interaction models, with enhanced capabilities across computer control, game environments, code generation, and tool use. It targets agentic workflows requiring robust multimodal understanding of graphical interfaces across diverse application domains.
7 months newer
DeepSeek-R1
DeepSeek
2025-01-20
UI-TARS-2
ByteDance
2025-09-04
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-R1
1 providers
DeepSeek
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UI-TARS-2
0 providers
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DeepSeek-R1
Avg Score:0.0%
Providers:1
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UI-TARS-2
Avg Score:0.0%
Providers:0