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.
Qwen2.5 7B Instruct
Alibaba
Qwen2.5 7B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 65.6% across 14 benchmarks. It excels particularly in GSM8k (91.6%), MT-Bench (87.5%), HumanEval (84.8%). The model shows particular specialization in math tasks with an average performance of 83.5%. It supports a 139K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.
Gemma 2 27B
2024-06-27
Qwen2.5 7B Instruct
Alibaba
2024-09-19
2 months newer
Performance Metrics
Context window and performance specifications
Gemma 2 27B
Qwen2.5 7B Instruct
Average performance across 4 common benchmarks
Gemma 2 27B
Qwen2.5 7B Instruct
Performance comparison across key benchmark categories
Gemma 2 27B
Qwen2.5 7B Instruct
Provider Availability & Performance
Available providers and their performance metrics
Gemma 2 27B
Qwen2.5 7B Instruct
Together
Gemma 2 27B
Qwen2.5 7B Instruct