Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 4.2% higher average benchmark score. Gemini 2.5 Pro offers 855.6K more tokens in context window than DeepSeek VL2. Gemini 2.5 Pro is $4798.25 cheaper per million tokens. 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.
Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
5 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Gemini 2.5 Pro
2025-05-20
Cost per million tokens (USD)
DeepSeek VL2
Gemini 2.5 Pro
Context window and performance specifications
Average performance across 29 common benchmarks
DeepSeek VL2
Gemini 2.5 Pro
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
DeepSeek VL2
Replicate
Gemini 2.5 Pro
DeepSeek VL2
Gemini 2.5 Pro
DeepSeek VL2
Gemini 2.5 Pro
ZeroEval