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-3

xAI

Grok-3 is a multimodal language model developed by xAI. This model demonstrates exceptional performance with an average score of 85.7% across 5 benchmarks. It excels particularly in AIME 2024 (93.3%), AIME 2025 (93.3%), GPQA (84.6%). The model shows particular specialization in general tasks with an average performance of 90.4%. 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 2025, it represents xAI's latest advancement in AI technology.

xAI

Grok-3

xAI

2025-02-17

Google

Gemma 3n E2B

Google

2025-06-26

4 months newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E2B

Max Context:-
Parameters:8.0B
xAI

Grok-3

Larger context
Max Context:136.0K

Performance comparison across key benchmark categories

Google

Gemma 3n E2B

general
54.1%
xAI

Grok-3

general
+36.3%
90.4%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E2B

2024-06-01

Grok-3

2024-11-17

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-3

1 providers

xAI

Throughput: 100 tok/s
Latency: 0.7ms
Google

Gemma 3n E2B

Avg Score:0.0%
Providers:0
xAI

Grok-3

Avg Score:0.0%
Providers:1