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DeepSeek-V3.2-Exp vs Gemma 2 9B
Comprehensive side-by-side LLM comparison
Gemma 2 9B leads with 3.6% higher average benchmark score. DeepSeek-V3.2-Exp is available on 2 providers. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3.2-Exp is a language model developed by DeepSeek. It achieves strong performance with an average score of 66.1% across 14 benchmarks. It excels particularly in SimpleQA (97.1%), AIME 2025 (89.3%), MMLU-Pro (85.0%). It supports a 229K token context window for handling large documents. The model is available through 2 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 2 9B is a language model developed by Google. It achieves strong performance with an average score of 64.6% across 16 benchmarks. It excels particularly in ARC-E (88.0%), BoolQ (84.2%), HellaSwag (81.9%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Google's latest advancement in AI technology.
1 year newer
Gemma 2 9B
2024-06-27
DeepSeek-V3.2-Exp
DeepSeek
2025-09-29
Performance Metrics
Context window and performance specifications
Average performance across 30 common benchmarks
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DeepSeek-V3.2-Exp
Average Score:30.8%
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Gemma 2 9B
Average Score:34.5%(+3.6%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.2-Exp
2 providers
Novita
ZeroEval
Throughput: 100 tok/s
Latency: 0.7ms
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Gemma 2 9B
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DeepSeek-V3.2-Exp
Avg Score:30.8%
Providers:2
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Gemma 2 9B
Avg Score:34.5%(+3.6%)
Providers:0