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.
Llama 3.1 Nemotron Ultra 253B v1
NVIDIA
Llama 3.1 Nemotron Ultra 253B v1 is a language model developed by NVIDIA. It achieves strong performance with an average score of 79.2% across 6 benchmarks. It excels particularly in MATH-500 (97.0%), IFEval (89.5%), GPQA (76.0%). Released in 2025, it represents NVIDIA's latest advancement in AI technology.
Llama 3.1 Nemotron Ultra 253B v1
NVIDIA
2025-04-07
Gemma 3n E2B Instructed LiteRT (Preview)
2025-05-20
1 month newer
Average performance across 3 common benchmarks
Gemma 3n E2B Instructed LiteRT (Preview)
Llama 3.1 Nemotron Ultra 253B v1
Performance comparison across key benchmark categories
Gemma 3n E2B Instructed LiteRT (Preview)
Llama 3.1 Nemotron Ultra 253B v1
Llama 3.1 Nemotron Ultra 253B v1
2023-12-01
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics
Gemma 3n E2B Instructed LiteRT (Preview)
Llama 3.1 Nemotron Ultra 253B v1
Gemma 3n E2B Instructed LiteRT (Preview)
Llama 3.1 Nemotron Ultra 253B v1