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.

Grok-4 Heavy
xAI
Grok-4 Heavy is a multimodal language model developed by xAI. It achieves strong performance with an average score of 79.5% across 6 benchmarks. It excels particularly in AIME 2025 (100.0%), HMMT25 (96.7%), GPQA (88.4%). The model shows particular specialization in general tasks with an average performance of 79.5%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents xAI's latest advancement in AI technology.

Gemma 3n E2B Instructed LiteRT (Preview)
2025-05-20

Grok-4 Heavy
xAI
2025-07-09
1 month newer
Average performance across 3 common benchmarks

Gemma 3n E2B Instructed LiteRT (Preview)

Grok-4 Heavy
Performance comparison across key benchmark categories

Gemma 3n E2B Instructed LiteRT (Preview)

Grok-4 Heavy
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
Grok-4 Heavy
2024-12-31
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E2B Instructed LiteRT (Preview)

Grok-4 Heavy

Gemma 3n E2B Instructed LiteRT (Preview)

Grok-4 Heavy