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DeepSeek VL2 vs Nemotron Nano 9B v2
Comprehensive side-by-side LLM comparison
DeepSeek VL2 supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-VL2 was developed as a vision-language model, designed to handle both visual and textual inputs for multimodal understanding tasks. Built to extend DeepSeek's capabilities beyond text-only processing, it enables applications requiring integrated analysis of images and language.
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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.
8 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Nemotron Nano 9B v2
NVIDIA
2025-08-18
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Performance Metrics
Context window and performance specifications
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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 VL2
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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Nemotron Nano 9B v2
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DeepSeek VL2
Avg Score:0.0%
Providers:1
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Nemotron Nano 9B v2
Avg Score:0.0%
Providers:0