Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 1.9% higher average benchmark score. DeepSeek-V3.1 offers 69.1K more tokens in context window than DeepSeek VL2. DeepSeek-V3.1 is $4808.23 cheaper per million tokens. DeepSeek VL2 supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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.
DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
28 days newer
DeepSeek VL2
DeepSeek
2024-12-13
DeepSeek-V3.1
DeepSeek
2025-01-10
Cost per million tokens (USD)
DeepSeek VL2
DeepSeek-V3.1
Context window and performance specifications
Average performance across 30 common benchmarks
DeepSeek VL2
DeepSeek-V3.1
Available providers and their performance metrics
DeepSeek VL2
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DeepSeek-V3.1
DeepSeek VL2
DeepSeek-V3.1
DeepSeek VL2
DeepSeek-V3.1
DeepInfra
Novita