Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash-Lite leads with 25.9% higher average benchmark score. Gemini 2.0 Flash-Lite offers 729.1K more tokens in context window than DeepSeek-V3 0324. Gemini 2.0 Flash-Lite is $1.05 cheaper per million tokens. Gemini 2.0 Flash-Lite supports multimodal inputs. Overall, Gemini 2.0 Flash-Lite is the stronger choice for coding tasks.
DeepSeek
DeepSeek-V3 0324 is a language model developed by DeepSeek. It achieves strong performance with an average score of 70.4% across 5 benchmarks. It excels particularly in MATH-500 (94.0%), MMLU-Pro (81.2%), GPQA (68.4%). It supports a 328K token context window for handling large documents. The model is available through 1 API provider. 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.
1 month newer
Gemini 2.0 Flash-Lite
2025-02-05
DeepSeek-V3 0324
DeepSeek
2025-03-25
Cost per million tokens (USD)
DeepSeek-V3 0324
Gemini 2.0 Flash-Lite
Context window and performance specifications
Average performance across 16 common benchmarks
DeepSeek-V3 0324
Gemini 2.0 Flash-Lite
Gemini 2.0 Flash-Lite
2024-06-01
Available providers and their performance metrics
DeepSeek-V3 0324
Novita
Gemini 2.0 Flash-Lite
DeepSeek-V3 0324
Gemini 2.0 Flash-Lite
DeepSeek-V3 0324
Gemini 2.0 Flash-Lite