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DeepSeek-R1 vs Qwen2.5-Coder 32B 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-Coder-32B-Instruct is a 32-billion-parameter code-specialized model from Alibaba, released in November 2024 and trained on a large corpus spanning 92 programming languages including C, Python, Java, Rust, and domain-specific languages. The model was designed to provide competitive code generation, repair, and reasoning capabilities as an open-weight alternative for developers building code assistant tools and automated review pipelines. Its 128K context window enables whole-file and multi-file code comprehension, making it particularly suited for complex repository-level tasks.
2 months newer
Qwen2.5-Coder 32B Instruct
Alibaba / Qwen
2024-11-12
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-Coder 32B Instruct
0 providers
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DeepSeek-R1
Avg Score:0.0%
Providers:1
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Qwen2.5-Coder 32B Instruct
Avg Score:0.0%
Providers:0