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DeepSeek-V3 vs Gemma 3n E2B
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 37.7% higher average benchmark score. Gemma 3n E2B supports multimodal inputs. Overall, DeepSeek-V3 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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Gemma 3N E2B was created as a specialized efficient variant, designed for deployment in edge and mobile environments with strict resource constraints. Built with optimizations for edge computing, it brings Gemma capabilities to devices and applications where traditional models would be impractical.
6 months newer
DeepSeek-V3
DeepSeek
2024-12-25
Gemma 3n E2B
2025-06-26
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-V3
Average Score:91.6%(+37.7%)
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Gemma 3n E2B
Average Score:53.9%
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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
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DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Gemma 3n E2B
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DeepSeek-V3
Avg Score:91.6%(+37.7%)
Providers:1
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Gemma 3n E2B
Avg Score:53.9%
Providers:0