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DeepSeek-V2.5 vs Llama 3.2 11B Instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 15.1% higher average benchmark score. Llama 3.2 11B Instruct offers 239.6K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Llama 3.2 11B Instruct supports multimodal inputs. Llama 3.2 11B Instruct is available on 6 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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Meta
Llama 3.2 11B was introduced as a mid-sized variant in the Llama 3.2 family, designed to offer enhanced capabilities while maintaining efficiency. Built to provide a balanced option for applications requiring more than lightweight models but less than flagship sizes, it serves diverse use cases in the open-source community.
4 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Llama 3.2 11B Instruct
Meta
2024-09-25
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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 3.2 11B Instruct
Input:$0.05
Output:$0.05($0.32 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V2.5
Average Score:77.6%(+15.1%)
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Llama 3.2 11B Instruct
Average Score:62.5%
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Knowledge Cutoff
Training data recency comparison
Llama 3.2 11B Instruct
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-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:77.6%(+15.1%)
Providers:3
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Llama 3.2 11B Instruct
Avg Score:62.5%
Providers:6