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Gemma 3n E2B vs Grok-3
Comprehensive side-by-side LLM comparison
Gemma 3n E2B leads with 13.5% higher average benchmark score. Overall, Gemma 3n E2B is the stronger choice for coding tasks.
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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.
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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 2025 (93.3%), AIME 2024 (93.3%), GPQA (84.6%). 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.
4 months newer
Grok-3
xAI
2025-02-17
Gemma 3n E2B
2025-06-26
Performance Metrics
Context window and performance specifications
Average performance across 16 common benchmarks
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Gemma 3n E2B
Average Score:40.3%(+13.5%)
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Grok-3
Average Score:26.8%
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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
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Gemma 3n E2B
0 providers
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Grok-3
1 providers
xAI
Throughput:
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Gemma 3n E2B
Avg Score:40.3%(+13.5%)
Providers:0
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Grok-3
Avg Score:26.8%
Providers:1