Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 8.7% higher average benchmark score. Gemini 2.0 Flash-Lite offers 798.2K more tokens in context window than DeepSeek VL2. Gemini 2.0 Flash-Lite is $4809.13 cheaper per million tokens. Overall, DeepSeek VL2 is the stronger choice for coding tasks.
DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). It supports a 259K token context window for handling large documents. 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 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
DeepSeek VL2
DeepSeek
2024-12-13
Gemini 2.0 Flash-Lite
2025-02-05
Cost per million tokens (USD)
DeepSeek VL2
Gemini 2.0 Flash-Lite
Context window and performance specifications
Average performance across 26 common benchmarks
DeepSeek VL2
Gemini 2.0 Flash-Lite
Gemini 2.0 Flash-Lite
2024-06-01
Available providers and their performance metrics
DeepSeek VL2
Replicate
Gemini 2.0 Flash-Lite
DeepSeek VL2
Gemini 2.0 Flash-Lite
DeepSeek VL2
Gemini 2.0 Flash-Lite