Model Comparison

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

DeepSeek

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.

Microsoft

Phi 4 Reasoning

Microsoft

Phi 4 Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 75.1% across 11 benchmarks. It excels particularly in FlenQA (97.7%), HumanEval+ (92.9%), IFEval (83.4%). The model shows particular specialization in code tasks with an average performance of 76.7%. 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

DeepSeek VL2 Tiny

DeepSeek

2024-12-13

Microsoft

Phi 4 Reasoning

Microsoft

2025-04-30

4 months newer

Performance comparison across key benchmark categories

DeepSeek

DeepSeek VL2 Tiny

math
53.6%
general
62.5%
Microsoft

Phi 4 Reasoning

math
+23.0%
76.6%
general
+11.7%
74.3%
Knowledge Cutoff
Training data recency comparison

Phi 4 Reasoning

2025-03-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek VL2 Tiny

0 providers
Microsoft

Phi 4 Reasoning

0 providers
DeepSeek

DeepSeek VL2 Tiny

Avg Score:0.0%
Providers:0
Microsoft

Phi 4 Reasoning

Avg Score:0.0%
Providers:0