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DeepSeek VL2 vs Llama 3.1 Nemotron 70B Instruct
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 9.8% 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 3.1 Nemotron 70B Instruct is a language model developed by NVIDIA. It achieves strong performance with an average score of 67.9% across 11 benchmarks. It excels particularly in GSM8k (91.4%), HellaSwag (85.6%), Winogrande (84.5%). Released in 2024, it represents NVIDIA's latest advancement in AI technology.
2 months newer
Llama 3.1 Nemotron 70B Instruct
NVIDIA
2024-10-01
DeepSeek VL2
DeepSeek
2024-12-13
Performance Metrics
Context window and performance specifications
Average performance across 25 common benchmarks
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DeepSeek VL2
Average Score:39.7%(+9.8%)
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Llama 3.1 Nemotron 70B Instruct
Average Score:29.9%
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Knowledge Cutoff
Training data recency comparison
Llama 3.1 Nemotron 70B Instruct
2023-12-01
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 3.1 Nemotron 70B Instruct
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DeepSeek VL2
Avg Score:39.7%(+9.8%)
Providers:1
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Llama 3.1 Nemotron 70B Instruct
Avg Score:29.9%
Providers:0