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

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.

Google

Gemma 3n E2B

Google

2025-06-26

xAI

Grok-4

xAI

2025-07-09

13 days newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E2B

Max Context:-
Parameters:8.0B
xAI

Grok-4

Larger context
Max Context:264.0K

Performance comparison across key benchmark categories

Google

Gemma 3n E2B

general
54.1%
reasoning
+50.7%
66.6%
xAI

Grok-4

general
+15.3%
69.3%
reasoning
15.9%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E2B

2024-06-01

Grok-4

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

2 providers

xAI

Throughput: 100 tok/s
Latency: 0.7ms

ZeroEval

Throughput: 100 tok/s
Latency: 0.7ms
Google

Gemma 3n E2B

Avg Score:0.0%
Providers:0
xAI

Grok-4

Avg Score:0.0%
Providers:2