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

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.

GPT-4.1 nano
OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). 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 2025, it represents OpenAI's latest advancement in AI technology.

Gemma 2 27B
2024-06-27

GPT-4.1 nano
OpenAI
2025-04-14
9 months newer
Performance Metrics
Context window and performance specifications

Gemma 2 27B

GPT-4.1 nano
Average performance across 1 common benchmarks

Gemma 2 27B

GPT-4.1 nano
Performance comparison across key benchmark categories

Gemma 2 27B

GPT-4.1 nano
GPT-4.1 nano
2024-05-31
Provider Availability & Performance
Available providers and their performance metrics

Gemma 2 27B

GPT-4.1 nano
OpenAI

Gemma 2 27B

GPT-4.1 nano