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

DeepSeek VL2 Tiny
DeepSeek
DeepSeek VL2 Tiny is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 63.1% across 14 benchmarks. It excels particularly in DocVQA (88.9%), ChartQA (81.0%), OCRBench (80.9%). 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-4-multimodal-instruct
Microsoft
Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). The model shows particular specialization in general tasks with an average performance of 75.8%. It supports a 256K 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. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.

DeepSeek VL2 Tiny
DeepSeek
2024-12-13

Phi-4-multimodal-instruct
Microsoft
2025-02-01
1 month newer
Performance Metrics
Context window and performance specifications

DeepSeek VL2 Tiny

Phi-4-multimodal-instruct
Average performance across 9 common benchmarks

DeepSeek VL2 Tiny

Phi-4-multimodal-instruct
Performance comparison across key benchmark categories

DeepSeek VL2 Tiny

Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek VL2 Tiny

Phi-4-multimodal-instruct
DeepInfra

DeepSeek VL2 Tiny

Phi-4-multimodal-instruct