Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 40.1% higher average benchmark score. Gemini 2.5 Pro offers 786.4K more tokens in context window than DeepSeek-V3 0324. DeepSeek-V3 0324 is $9.83 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Overall, Gemini 2.5 Pro is the stronger choice for coding tasks.
DeepSeek
DeepSeek-V3 0324 is a language model developed by DeepSeek. It achieves strong performance with an average score of 70.4% across 5 benchmarks. It excels particularly in MATH-500 (94.0%), MMLU-Pro (81.2%), GPQA (68.4%). It supports a 328K token context window for handling large documents. The model is available through 1 API provider. Released in 2025, 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.
1 month newer
DeepSeek-V3 0324
DeepSeek
2025-03-25
Gemini 2.5 Pro
2025-05-20
Cost per million tokens (USD)
DeepSeek-V3 0324
Gemini 2.5 Pro
Context window and performance specifications
Average performance across 19 common benchmarks
DeepSeek-V3 0324
Gemini 2.5 Pro
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
DeepSeek-V3 0324
Novita
Gemini 2.5 Pro
DeepSeek-V3 0324
Gemini 2.5 Pro
DeepSeek-V3 0324
Gemini 2.5 Pro
ZeroEval