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DeepSeek-R1-0528 vs Gemma 3n E2B
Comprehensive side-by-side LLM comparison
DeepSeek-R1-0528 leads with 11.7% higher average benchmark score. Gemma 3n E2B supports multimodal inputs. DeepSeek-R1-0528 is available on 3 providers. Overall, DeepSeek-R1-0528 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-R1-0528 is a language model developed by DeepSeek. It achieves strong performance with an average score of 60.1% across 16 benchmarks. It excels particularly in MMLU-Redux (93.4%), SimpleQA (92.3%), AIME 2024 (91.4%). It supports a 262K token context window for handling large documents. The model is available through 3 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
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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.
29 days newer
DeepSeek-R1-0528
DeepSeek
2025-05-28
Gemma 3n E2B
2025-06-26
Performance Metrics
Context window and performance specifications
Average performance across 27 common benchmarks
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DeepSeek-R1-0528
Average Score:35.6%(+11.7%)
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Gemma 3n E2B
Average Score:23.9%
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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-R1-0528
3 providers
DeepInfra
Throughput: 45.04 tok/s
Latency: 0.61ms
DeepSeek
Throughput: 9 tok/s
Latency: 0.3ms
Novita
Throughput: 37.96 tok/s
Latency: 1.18ms
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DeepSeek-R1-0528
Avg Score:35.6%(+11.7%)
Providers:3
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Gemma 3n E2B
Avg Score:23.9%
Providers:0