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 2 27B
Gemma 2 27B is a language model developed by Google. It achieves strong performance with an average score of 69.1% across 16 benchmarks. It excels particularly in ARC-E (88.6%), HellaSwag (86.4%), BoolQ (84.8%). The model shows particular specialization in reasoning tasks with an average performance of 82.5%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Google's latest advancement in AI technology.

Gemma 2 27B
2024-06-27

DeepSeek-V3.1
DeepSeek
2025-01-10
6 months newer
Performance Metrics
Context window and performance specifications

DeepSeek-V3.1

Gemma 2 27B
Performance comparison across key benchmark categories

DeepSeek-V3.1

Gemma 2 27B
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek-V3.1
DeepInfra
Novita

Gemma 2 27B

DeepSeek-V3.1

Gemma 2 27B