Comprehensive side-by-side LLM comparison
DeepSeek-V3.1 leads with 6.5% higher average benchmark score. Gemini 2.0 Flash-Lite offers 729.1K more tokens in context window than DeepSeek-V3.1. Gemini 2.0 Flash-Lite is $0.90 cheaper per million tokens. Gemini 2.0 Flash-Lite supports multimodal inputs. Overall, DeepSeek-V3.1 is the stronger choice for coding tasks.
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 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). 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.
26 days newer
DeepSeek-V3.1
DeepSeek
2025-01-10
Gemini 2.0 Flash-Lite
2025-02-05
Cost per million tokens (USD)
DeepSeek-V3.1
Gemini 2.0 Flash-Lite
Context window and performance specifications
Average performance across 26 common benchmarks
DeepSeek-V3.1
Gemini 2.0 Flash-Lite
Gemini 2.0 Flash-Lite
2024-06-01
Available providers and their performance metrics
DeepSeek-V3.1
DeepInfra
Novita
Gemini 2.0 Flash-Lite
DeepSeek-V3.1
Gemini 2.0 Flash-Lite
DeepSeek-V3.1
Gemini 2.0 Flash-Lite