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DeepSeek-R1-0528 vs Nemotron Nano 9B v2
Comprehensive side-by-side LLM comparison
DeepSeek-R1-0528 leads with 11.5% higher average benchmark score. 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 represents a specific release iteration of the DeepSeek-R1 model, developed to incorporate refinements and improvements from ongoing training. Built to provide enhanced reasoning capabilities based on accumulated insights, it continues the evolution of DeepSeek's reasoning-focused architecture.
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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.
2 months newer
DeepSeek-R1-0528
DeepSeek
2025-05-28
Nemotron Nano 9B v2
NVIDIA
2025-08-18
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-R1-0528
Average Score:80.6%(+11.5%)
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Nemotron Nano 9B v2
Average Score:69.1%
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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-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:80.6%(+11.5%)
Providers:3
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Nemotron Nano 9B v2
Avg Score:69.1%
Providers:0