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

Gemma 3n E2B Instructed LiteRT (Preview)
Gemma 3n E2B Instructed LiteRT (Preview) is a multimodal language model developed by Google. The model shows competitive results across 28 benchmarks. Notable strengths include PIQA (78.9%), BoolQ (76.4%), ARC-E (75.8%). 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 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 LiteRT (Preview)
2025-05-20
2 months newer
Average performance across 2 common benchmarks

Gemma 3n E2B Instructed LiteRT (Preview)

QwQ-32B
Performance comparison across key benchmark categories

Gemma 3n E2B Instructed LiteRT (Preview)

QwQ-32B
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
QwQ-32B
2024-11-28
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E2B Instructed LiteRT (Preview)

QwQ-32B

Gemma 3n E2B Instructed LiteRT (Preview)

QwQ-32B