Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 26.5% higher average benchmark score. DeepSeek VL2 offers 217.6K more tokens in context window than Gemini 1.0 Pro. Gemini 1.0 Pro is $4807.50 cheaper per million tokens. DeepSeek VL2 supports multimodal inputs. 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 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.
10 months newer
Gemini 1.0 Pro
2024-02-15
DeepSeek VL2
DeepSeek
2024-12-13
Cost per million tokens (USD)
DeepSeek VL2
Gemini 1.0 Pro
Context window and performance specifications
Average performance across 21 common benchmarks
DeepSeek VL2
Gemini 1.0 Pro
Gemini 1.0 Pro
2024-02-01
Available providers and their performance metrics
DeepSeek VL2
Replicate
Gemini 1.0 Pro
DeepSeek VL2
Gemini 1.0 Pro
DeepSeek VL2
Gemini 1.0 Pro