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DeepSeek-R1 vs Qwen2.5 72B Instruct
Comprehensive side-by-side LLM comparison
. 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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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.
4 months newer
Qwen2.5 72B Instruct
Alibaba / Qwen
2024-09-19
DeepSeek-R1
DeepSeek
2025-01-20
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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Qwen2.5 72B Instruct
0 providers
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DeepSeek-R1
Avg Score:0.0%
Providers:1
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Qwen2.5 72B Instruct
Avg Score:0.0%
Providers:0