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
xAI
Grok-4 is a multimodal language model developed by xAI. It achieves strong performance with an average score of 63.1% across 7 benchmarks. It excels particularly in AIME 2025 (91.7%), HMMT25 (90.0%), GPQA (87.5%). It supports a 264K token context window for handling large documents. The model is available through 2 API providers. 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
xAI
2025-07-09
1 month newer
Performance Metrics
Context window and performance specifications

Gemma 3n E2B Instructed LiteRT (Preview)

Grok-4
Average performance across 3 common benchmarks

Gemma 3n E2B Instructed LiteRT (Preview)

Grok-4
Performance comparison across key benchmark categories

Gemma 3n E2B Instructed LiteRT (Preview)

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

Gemma 3n E2B Instructed LiteRT (Preview)

Grok-4
xAI
ZeroEval

Gemma 3n E2B Instructed LiteRT (Preview)

Grok-4