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-2

xAI

Grok-2 is a multimodal language model developed by xAI. It achieves strong performance with an average score of 76.5% across 8 benchmarks. It excels particularly in DocVQA (93.6%), HumanEval (88.4%), MMLU (87.5%). It supports a 136K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents xAI's latest advancement in AI technology.

xAI

Grok-2

xAI

2024-08-13

Google

Gemma 3n E2B

Google

2025-06-26

10 months newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E2B

Max Context:-
Parameters:8.0B
xAI

Grok-2

Larger context
Max Context:136.0K

Performance comparison across key benchmark categories

Google

Gemma 3n E2B

general
54.1%
xAI

Grok-2

general
+18.9%
73.0%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E2B

2024-06-01

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-2

1 providers

xAI

Throughput: 85 tok/s
Latency: 0.7ms
Google

Gemma 3n E2B

Avg Score:0.0%
Providers:0
xAI

Grok-2

Avg Score:0.0%
Providers:1