Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 19.9% higher average benchmark score. Gemini 2.5 Flash-Lite offers 1.1M more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Gemini 2.5 Flash-Lite supports multimodal inputs. DeepSeek-V2.5 is available on 3 providers. Overall, DeepSeek-V2.5 is the stronger choice for coding tasks.
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 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in FACTS Grounding (84.1%), Global-MMLU-Lite (81.1%), MMMU (72.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 2025, it represents Google's latest advancement in AI technology.
1 year newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Gemini 2.5 Flash-Lite
2025-06-17
Cost per million tokens (USD)
DeepSeek-V2.5
Gemini 2.5 Flash-Lite
Context window and performance specifications
Average performance across 27 common benchmarks
DeepSeek-V2.5
Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite
2025-01-01
Available providers and their performance metrics
DeepSeek-V2.5
DeepInfra
DeepSeek
Hyperbolic
DeepSeek-V2.5
Gemini 2.5 Flash-Lite
DeepSeek-V2.5
Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite