+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
DeepSeek-R1 vs Qwen2.5-Coder 7B Instruct
Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
+
+
+
+
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.
+
+
+
+
Alibaba / Qwen
Qwen2.5-Coder-7B-Instruct is a 7-billion-parameter code-specialized model from Alibaba, released in November 2024 as part of the Qwen2.5-Coder family, trained on a curated corpus spanning 92 programming languages with emphasis on code generation, debugging, and fill-in-the-middle completion. Built on the Qwen2.5 architecture, it extends the base series' improvements in instruction-following and long-context handling to coding-specific tasks within a compact deployable footprint. It became popular for integration into IDE extensions, CI pipelines, and self-hosted code assistant tools.
2 months newer
Qwen2.5-Coder 7B 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
+
+
+
+
DeepSeek-R1
1 providers
DeepSeek
+
+
+
+
Qwen2.5-Coder 7B Instruct
0 providers
+
+
+
+
DeepSeek-R1
Avg Score:0.0%
Providers:1
+
+
+
+
Qwen2.5-Coder 7B Instruct
Avg Score:0.0%
Providers:0