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

Gemini 2.0 Flash
Gemini 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Google'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

Gemini 2.0 Flash
2024-12-01
3 months newer
Performance Metrics
Context window and performance specifications

Gemini 2.0 Flash

Phi-3.5-MoE-instruct
Average performance across 3 common benchmarks

Gemini 2.0 Flash

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

Gemini 2.0 Flash

Phi-3.5-MoE-instruct
Gemini 2.0 Flash
2024-08-01
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.0 Flash

Phi-3.5-MoE-instruct

Gemini 2.0 Flash

Phi-3.5-MoE-instruct