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DeepSeek-V3 vs Llama 3.1 405B Instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 3.3% higher average benchmark score. DeepSeek-V3 offers 6.1K more tokens in context window than Llama 3.1 405B Instruct. Both models have similar pricing. Llama 3.1 405B Instruct is available on 8 providers. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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Meta
Llama 3.1 405B was developed as Meta's largest open-source language model, designed to provide frontier-level capabilities with 405 billion parameters. Built to demonstrate that open-source models can match proprietary systems in capability, it enables researchers and developers to experiment with and deploy a powerful foundation model without licensing restrictions.
5 months newer
Llama 3.1 405B Instruct
Meta
2024-07-23
DeepSeek-V3
DeepSeek
2024-12-25
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3
Input:$0.27
Output:$1.10($0.41 cheaper)
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Llama 3.1 405B Instruct
Input:$0.89
Output:$0.89
Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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DeepSeek-V3
Average Score:80.2%(+3.3%)
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Llama 3.1 405B Instruct
Average Score:76.9%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Llama 3.1 405B Instruct
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DeepSeek-V3
Avg Score:80.2%(+3.3%)
Providers:1
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Llama 3.1 405B Instruct
Avg Score:76.9%
Providers:8