Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Gemini 2.5 Flash offers 786.4K more tokens in context window than DeepSeek-V3.1. DeepSeek-V3.1 is $1.53 cheaper per million tokens. Gemini 2.5 Flash supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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.
Gemini 2.5 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 14 benchmarks. It excels particularly in Global-MMLU-Lite (88.4%), AIME 2024 (88.0%), FACTS Grounding (85.3%). 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.
4 months newer
DeepSeek-V3.1
DeepSeek
2025-01-10
Gemini 2.5 Flash
2025-05-20
Cost per million tokens (USD)
DeepSeek-V3.1
Gemini 2.5 Flash
Context window and performance specifications
Average performance across 22 common benchmarks
DeepSeek-V3.1
Gemini 2.5 Flash
Gemini 2.5 Flash
2025-01-31
Available providers and their performance metrics
DeepSeek-V3.1
DeepInfra
Novita
Gemini 2.5 Flash
DeepSeek-V3.1
Gemini 2.5 Flash
DeepSeek-V3.1
Gemini 2.5 Flash
ZeroEval