Model Comparison

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

Google

Gemma 3n E2B

Google

Gemma 3n E2B is a multimodal language model developed by Google. The model shows competitive results across 11 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. Released in 2025, it represents Google's latest advancement in AI technology.

xAI

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.

Google

Gemma 3n E2B

Google

2025-06-26

xAI

Grok-4 Heavy

xAI

2025-07-09

13 days newer

Performance comparison across key benchmark categories

Google

Gemma 3n E2B

general
54.1%
xAI

Grok-4 Heavy

general
+25.5%
79.5%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E2B

2024-06-01

Grok-4 Heavy

2024-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 3n E2B

0 providers
xAI

Grok-4 Heavy

0 providers
Google

Gemma 3n E2B

Avg Score:0.0%
Providers:0
xAI

Grok-4 Heavy

Avg Score:0.0%
Providers:0