Model Comparison

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

Gemma 2 27B

Google

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-Omni-7B

Alibaba

Qwen2.5-Omni-7B is a multimodal language model developed by Alibaba. The model shows competitive results across 45 benchmarks. It excels particularly in DocVQA (95.2%), VocalSound (93.9%), GSM8k (88.7%). The model shows particular specialization in code tasks with an average performance of 76.0%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Gemma 2 27B

Google

2024-06-27

Qwen2.5-Omni-7B

Alibaba

2025-03-27

9 months newer

Average performance across 4 common benchmarks

Gemma 2 27B

Average Score:57.7%

Qwen2.5-Omni-7B

+20.3%

Average Score:78.0%

Performance comparison across key benchmark categories

Gemma 2 27B

code

56.5%

general

+11.3%

70.0%

math

58.1%

Qwen2.5-Omni-7B

code

+19.5%

76.0%

general

58.7%

math

+5.1%

63.3%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

Gemma 2 27B

0 providers

Qwen2.5-Omni-7B

0 providers

Gemma 2 27B

Avg Score:57.7%

Providers:0

Qwen2.5-Omni-7B

+20.3%

Avg Score:78.0%

Providers:0