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DeepSeek R1 Distill Qwen 32B vs Gemma 3n E4B
Comprehensive side-by-side LLM comparison
Gemma 3n E4B leads with 27.6% higher average benchmark score. Gemma 3n E4B supports multimodal inputs. Overall, Gemma 3n E4B is the stronger choice for coding tasks.
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DeepSeek
DeepSeek R1 Distill Qwen 32B is a language model developed by DeepSeek. It achieves strong performance with an average score of 74.2% across 4 benchmarks. It excels particularly in MATH-500 (94.3%), AIME 2024 (83.3%), GPQA (62.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. 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 E4B is a multimodal language model developed by Google. It achieves strong performance with an average score of 64.6% across 11 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). 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.
5 months newer
DeepSeek R1 Distill Qwen 32B
DeepSeek
2025-01-20
Gemma 3n E4B
2025-06-26
Performance Metrics
Context window and performance specifications
Average performance across 15 common benchmarks
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DeepSeek R1 Distill Qwen 32B
Average Score:19.8%
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Gemma 3n E4B
Average Score:47.4%(+27.6%)
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E4B
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 Distill Qwen 32B
1 providers
DeepInfra
Throughput: 37 tok/s
Latency: 0.65ms
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Gemma 3n E4B
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DeepSeek R1 Distill Qwen 32B
Avg Score:19.8%
Providers:1
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Gemma 3n E4B
Avg Score:47.4%(+27.6%)
Providers:0