Model Comparison
Comprehensive side-by-side analysis of model capabilities and performance

DeepSeek VL2 Small
DeepSeek
DeepSeek VL2 Small is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 69.6% across 14 benchmarks. It excels particularly in DocVQA (92.3%), ChartQA (84.5%), OCRBench (83.4%). 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.

Phi-3.5-vision-instruct
Microsoft
Phi-3.5-vision-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 68.3% across 9 benchmarks. It excels particularly in ScienceQA (91.3%), POPE (86.1%), MMBench (81.9%). The model shows particular specialization in general tasks with an average performance of 75.9%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Phi-3.5-vision-instruct
Microsoft
2024-08-23

DeepSeek VL2 Small
DeepSeek
2024-12-13
3 months newer
Average performance across 6 common benchmarks

DeepSeek VL2 Small

Phi-3.5-vision-instruct
Performance comparison across key benchmark categories

DeepSeek VL2 Small

Phi-3.5-vision-instruct
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek VL2 Small

Phi-3.5-vision-instruct

DeepSeek VL2 Small

Phi-3.5-vision-instruct