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.
Gemma 3n E2B Instructed
Gemma 3n E2B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (66.5%), MMLU (60.1%), Global-MMLU-Lite (59.0%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
DeepSeek-V3.1
DeepSeek
2025-01-10
Gemma 3n E2B Instructed
2025-06-26
5 months newer
Performance Metrics
Context window and performance specifications
DeepSeek-V3.1
Gemma 3n E2B Instructed
Average performance across 3 common benchmarks
DeepSeek-V3.1
Gemma 3n E2B Instructed
Performance comparison across key benchmark categories
DeepSeek-V3.1
Gemma 3n E2B Instructed
Gemma 3n E2B Instructed
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics
DeepSeek-V3.1
DeepInfra
Novita
Gemma 3n E2B Instructed
DeepSeek-V3.1
Gemma 3n E2B Instructed