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DeepSeek-V2.5 vs Llama 3.1 Nemotron 70B Instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 28.4% higher average benchmark score. DeepSeek-V2.5 is available on 3 providers. Overall, DeepSeek-V2.5 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V2.5 was developed as an enhanced iteration of the DeepSeek-V2 architecture, designed to incorporate improvements in model quality and efficiency. Built to advance the DeepSeek foundation model series, it provides refined capabilities for general-purpose language understanding and generation tasks.
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NVIDIA
Llama 3.1 Nemotron 70B was developed by NVIDIA through customization of Meta's Llama 3.1 70B, designed to enhance performance for specific use cases and deployments. Built with NVIDIA's optimizations and fine-tuning expertise, it demonstrates how foundation models can be adapted for specialized applications.
4 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Llama 3.1 Nemotron 70B Instruct
NVIDIA
2024-10-01
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-V2.5
Average Score:88.6%(+28.4%)
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Llama 3.1 Nemotron 70B Instruct
Average Score:60.2%
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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-V2.5
3 providers
DeepInfra
Throughput: 63 tok/s
Latency: 0.5ms
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 100 tok/s
Latency: 0.5ms
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DeepSeek-V2.5
Avg Score:88.6%(+28.4%)
Providers:3
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Llama 3.1 Nemotron 70B Instruct
Avg Score:60.2%
Providers:0