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-3.5-MoE-instruct

Microsoft

Phi-3.5-MoE-instruct is a language model developed by Microsoft. It achieves strong performance with an average score of 65.6% across 31 benchmarks. It excels particularly in ARC-C (91.0%), OpenBookQA (89.6%), GSM8k (88.7%). The model shows particular specialization in reasoning tasks with an average performance of 85.4%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Microsoft

Phi-3.5-MoE-instruct

Microsoft

2024-08-23

DeepSeek

DeepSeek VL2 Tiny

DeepSeek

2024-12-13

3 months newer

Performance comparison across key benchmark categories

DeepSeek

DeepSeek VL2 Tiny

math
53.6%
general
+1.6%
62.5%
Microsoft

Phi-3.5-MoE-instruct

math
+15.4%
69.0%
general
60.9%

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek VL2 Tiny

0 providers
Microsoft

Phi-3.5-MoE-instruct

0 providers
DeepSeek

DeepSeek VL2 Tiny

Avg Score:0.0%
Providers:0
Microsoft

Phi-3.5-MoE-instruct

Avg Score:0.0%
Providers:0