Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 7.4% higher average benchmark score. Gemini 2.0 Flash offers 1.0M more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Gemini 2.0 Flash 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 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). 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 2024, it represents Google's latest advancement in AI technology.
6 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Gemini 2.0 Flash
2024-12-01
Cost per million tokens (USD)
DeepSeek-V2.5
Gemini 2.0 Flash
Context window and performance specifications
Average performance across 27 common benchmarks
DeepSeek-V2.5
Gemini 2.0 Flash
Gemini 2.0 Flash
2024-08-01
Available providers and their performance metrics
DeepSeek-V2.5
DeepInfra
DeepSeek
Hyperbolic
DeepSeek-V2.5
Gemini 2.0 Flash
DeepSeek-V2.5
Gemini 2.0 Flash
Gemini 2.0 Flash