Model Comparison

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

Google

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.

Microsoft

Phi 4 Mini

Microsoft

Phi 4 Mini is a language model developed by Microsoft. It achieves strong performance with an average score of 65.4% across 17 benchmarks. It excels particularly in GSM8k (88.6%), ARC-C (83.7%), BoolQ (81.2%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.

Google

Gemma 2 27B

Google

2024-06-27

Microsoft

Phi 4 Mini

Microsoft

2025-02-01

7 months newer

Average performance across 9 common benchmarks

Google

Gemma 2 27B

Average Score:72.7%
Microsoft

Phi 4 Mini

+1.8%
Average Score:74.6%

Performance comparison across key benchmark categories

Google

Gemma 2 27B

reasoning
+9.3%
82.5%
math
58.1%
general
+9.2%
70.0%
Microsoft

Phi 4 Mini

reasoning
73.3%
math
+14.0%
72.2%
general
60.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Phi 4 Mini

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 2 27B

0 providers
Microsoft

Phi 4 Mini

0 providers
Google

Gemma 2 27B

Avg Score:72.7%
Providers:0
Microsoft

Phi 4 Mini

+1.8%
Avg Score:74.6%
Providers:0