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DeepSeek-R1 vs Qwen2.5-VL 32B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5-VL 32B Instruct 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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Alibaba / Qwen
Qwen2.5-VL-32B-Instruct is a 32-billion-parameter vision-language model from Alibaba, extending the Qwen2.5 architecture with multimodal capabilities for understanding images, documents, charts, and video frames alongside text. The model was designed for tasks requiring deep visual reasoning — such as document parsing, table extraction, and spatial understanding — with performance that made it a practical choice for document intelligence and visual data analysis workflows. As an open-weight model, it became a widely adopted foundation for fine-tuning domain-specific multimodal applications.
1 month newer
DeepSeek-R1
DeepSeek
2025-01-20
Qwen2.5-VL 32B Instruct
Alibaba / Qwen
2025-03-01
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-VL 32B Instruct
0 providers
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DeepSeek-R1
Avg Score:0.0%
Providers:1
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Qwen2.5-VL 32B Instruct
Avg Score:0.0%
Providers:0