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DeepSeek VL2 vs Llama-3.3 Nemotron Super 49B v1
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 20.3% higher average benchmark score. DeepSeek VL2 supports multimodal inputs. Overall, DeepSeek VL2 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). It supports a 259K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
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NVIDIA
Llama-3.3 Nemotron Super 49B v1 is a language model developed by NVIDIA. This model demonstrates exceptional performance with an average score of 81.0% across 7 benchmarks. It excels particularly in MATH-500 (96.6%), MT-Bench (91.7%), MBPP (91.3%). Released in 2025, it represents NVIDIA's latest advancement in AI technology.
3 months newer
DeepSeek VL2
DeepSeek
2024-12-13
Llama-3.3 Nemotron Super 49B v1
NVIDIA
2025-03-18
Performance Metrics
Context window and performance specifications
Average performance across 21 common benchmarks
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DeepSeek VL2
Average Score:47.3%(+20.3%)
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Llama-3.3 Nemotron Super 49B v1
Average Score:27.0%
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Knowledge Cutoff
Training data recency comparison
Llama-3.3 Nemotron Super 49B v1
2023-12-31
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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Llama-3.3 Nemotron Super 49B v1
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DeepSeek VL2
Avg Score:47.3%(+20.3%)
Providers:1
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Llama-3.3 Nemotron Super 49B v1
Avg Score:27.0%
Providers:0