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DeepSeek-V2.5 vs Llama 3.3 70B Instruct
Comprehensive side-by-side LLM comparison
Llama 3.3 70B Instruct leads with 2.4% higher average benchmark score. Llama 3.3 70B Instruct offers 239.6K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Llama 3.3 70B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
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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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Meta
Llama 3.3 70B was introduced with refinements to the Llama 3 architecture, designed to incorporate improvements in instruction-following and task performance. Built to continue the evolution of Meta's 70B tier, it provides enhanced quality while maintaining the deployment characteristics valued by the open-source community.
7 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Llama 3.3 70B Instruct
Meta
2024-12-06
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28
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Llama 3.3 70B Instruct
Input:$0.20
Output:$0.20($0.02 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-V2.5
Average Score:81.4%
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Llama 3.3 70B Instruct
Average Score:83.8%(+2.4%)
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:81.4%
Providers:3
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Llama 3.3 70B Instruct
Avg Score:83.8%(+2.4%)
Providers:9