Model Comparison
Comprehensive side-by-side analysis of model capabilities and performance
DeepSeek-V3.1
DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). The model shows particular specialization in factuality tasks with an average performance of 92.6%. It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
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.
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
DeepSeek-V3.1
DeepSeek
2025-01-10
4 months newer
Performance Metrics
Context window and performance specifications
DeepSeek-V3.1
Phi-3.5-MoE-instruct
Average performance across 1 common benchmarks
DeepSeek-V3.1
Phi-3.5-MoE-instruct
Performance comparison across key benchmark categories
DeepSeek-V3.1
Phi-3.5-MoE-instruct
Provider Availability & Performance
Available providers and their performance metrics
DeepSeek-V3.1
DeepInfra
Novita
Phi-3.5-MoE-instruct
DeepSeek-V3.1
Phi-3.5-MoE-instruct