Model Comparison

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

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.

QwQ-32B

Alibaba

QwQ-32B is a language model developed by Alibaba. It achieves strong performance with an average score of 74.6% across 7 benchmarks. It excels particularly in MATH-500 (90.6%), IFEval (83.9%), AIME 2024 (79.5%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

QwQ-32B

Alibaba

2025-03-05

Gemma 3n E2B Instructed

Google

2025-06-26

3 months newer

Average performance across 2 common benchmarks

Gemma 3n E2B Instructed

Average Score:19.0%

QwQ-32B

+45.3%

Average Score:64.3%

Performance comparison across key benchmark categories

Gemma 3n E2B Instructed

math

40.4%

code

33.2%

general

32.8%

QwQ-32B

math

+50.2%

90.6%

code

+40.5%

73.6%

general

+37.6%

70.4%

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

QwQ-32B

2024-11-28

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Gemma 3n E2B Instructed

0 providers

QwQ-32B

0 providers

Gemma 3n E2B Instructed

Avg Score:19.0%

Providers:0

QwQ-32B

+45.3%

Avg Score:64.3%

Providers:0