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DeepSeek VL2 vs Magistral Small 2506
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 41.1% higher average benchmark score. DeepSeek VL2 supports multimodal inputs. Overall, DeepSeek VL2 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). It supports a 259K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
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Mistral AI
Magistral Small 2506 is a language model developed by Mistral AI. It achieves strong performance with an average score of 63.2% across 4 benchmarks. Notable strengths include AIME 2024 (70.7%), GPQA (68.2%), AIME 2025 (62.8%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Mistral AI's latest advancement in AI technology.
5 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Magistral Small 2506
Mistral AI
2025-06-10
Performance Metrics
Context window and performance specifications
Average performance across 18 common benchmarks
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DeepSeek VL2
Average Score:55.1%(+41.1%)
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Magistral Small 2506
Average Score:14.1%
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Knowledge Cutoff
Training data recency comparison
Magistral Small 2506
2025-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek VL2
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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Magistral Small 2506
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DeepSeek VL2
Avg Score:55.1%(+41.1%)
Providers:1
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Magistral Small 2506
Avg Score:14.1%
Providers:0