Model Comparison

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

DeepSeek

DeepSeek R1 Zero

DeepSeek

DeepSeek R1 Zero is a language model developed by DeepSeek. It achieves strong performance with an average score of 76.5% across 4 benchmarks. It excels particularly in MATH-500 (95.9%), AIME 2024 (86.7%), GPQA (73.3%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

Google

Gemma 3n E2B Instructed

Google

Gemma 3n E2B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (66.5%), MMLU (60.1%), Global-MMLU-Lite (59.0%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

DeepSeek

DeepSeek R1 Zero

DeepSeek

2025-01-20

Google

Gemma 3n E2B Instructed

Google

2025-06-26

5 months newer

Average performance across 2 common benchmarks

DeepSeek

DeepSeek R1 Zero

+42.7%
Average Score:61.7%
Google

Gemma 3n E2B Instructed

Average Score:19.0%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek R1 Zero

math
+55.5%
95.9%
general
+47.2%
80.0%
code
+16.8%
50.0%
Google

Gemma 3n E2B Instructed

math
40.4%
general
32.8%
code
33.2%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemma 3n E2B Instructed

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek R1 Zero

0 providers
Google

Gemma 3n E2B Instructed

0 providers
DeepSeek

DeepSeek R1 Zero

+42.7%
Avg Score:61.7%
Providers:0
Google

Gemma 3n E2B Instructed

Avg Score:19.0%
Providers:0