Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 1.6% higher average benchmark score. Gemini 2.5 Pro offers 1.1M more tokens in context window than DeepSeek-V2.5. DeepSeek-V2.5 is $10.83 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-V2.5 is a language model developed by DeepSeek. It achieves strong performance with an average score of 71.1% across 15 benchmarks. It excels particularly in GSM8k (95.1%), MT-Bench (90.2%), HumanEval (89.0%). The model is available through 3 API providers. 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.
1 year newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Gemini 2.5 Pro
2025-05-20
Cost per million tokens (USD)
DeepSeek-V2.5
Gemini 2.5 Pro
Context window and performance specifications
Average performance across 30 common benchmarks
DeepSeek-V2.5
Gemini 2.5 Pro
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
DeepSeek-V2.5
DeepInfra
DeepSeek
Hyperbolic
DeepSeek-V2.5
Gemini 2.5 Pro
DeepSeek-V2.5
Gemini 2.5 Pro
Gemini 2.5 Pro
ZeroEval