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DeepSeek-V3 vs Nemotron Nano 9B v2
Comprehensive side-by-side LLM comparison
Nemotron Nano 9B v2 leads with 12.6% higher average benchmark score. Overall, Nemotron Nano 9B v2 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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NVIDIA
Nemotron Nano 9B v2 is a language model developed by NVIDIA. It achieves strong performance with an average score of 77.0% across 6 benchmarks. It excels particularly in MATH-500 (97.8%), IFEval (90.3%), AIME 2025 (72.1%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents NVIDIA's latest advancement in AI technology.
7 months newer
DeepSeek-V3
DeepSeek
2024-12-25
Nemotron Nano 9B v2
NVIDIA
2025-08-18
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Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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DeepSeek-V3
Average Score:68.3%
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Nemotron Nano 9B v2
Average Score:80.8%(+12.6%)
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Knowledge Cutoff
Training data recency comparison
Nemotron Nano 9B v2
2024-09
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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Nemotron Nano 9B v2
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DeepSeek-V3
Avg Score:68.3%
Providers:1
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Nemotron Nano 9B v2
Avg Score:80.8%(+12.6%)
Providers:0