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DeepSeek-V3 vs Gemma 3n E2B Instructed LiteRT (Preview)
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 2.6% higher average benchmark score. Gemma 3n E2B Instructed LiteRT (Preview) supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3 is a language model developed by DeepSeek. It achieves strong performance with an average score of 67.2% across 20 benchmarks. It excels particularly in DROP (91.6%), CLUEWSC (90.9%), MATH-500 (90.2%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
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Gemma 3n E2B Instructed LiteRT (Preview) is a multimodal language model developed by Google. The model shows competitive results across 28 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. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.
4 months newer
DeepSeek-V3
DeepSeek
2024-12-25
Gemma 3n E2B Instructed LiteRT (Preview)
2025-05-20
Performance Metrics
Context window and performance specifications
Average performance across 43 common benchmarks
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DeepSeek-V3
Average Score:31.2%(+2.6%)
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Gemma 3n E2B Instructed LiteRT (Preview)
Average Score:28.6%
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E2B Instructed LiteRT (Preview)
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 Instructed LiteRT (Preview)
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DeepSeek-V3
Avg Score:31.2%(+2.6%)
Providers:1
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Gemma 3n E2B Instructed LiteRT (Preview)
Avg Score:28.6%
Providers:0