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DeepSeek-V2.5 vs Llama 3.2 90B Instruct
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Llama 3.2 90B Instruct offers 239.6K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Llama 3.2 90B Instruct supports multimodal inputs. Llama 3.2 90B Instruct is available on 5 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 3.2 90B was developed as a flagship-tier open-source model, designed to provide advanced capabilities with 90 billion parameters. Built to serve applications requiring high-quality reasoning and generation, it represents a powerful option within the Llama 3.2 series for demanding tasks.
4 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Llama 3.2 90B 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($0.33 cheaper)
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Llama 3.2 90B Instruct
Input:$0.35
Output:$0.40
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V2.5
Average Score:77.6%(+0.6%)
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Llama 3.2 90B Instruct
Average Score:77.0%
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%(+0.6%)
Providers:3
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Llama 3.2 90B Instruct
Avg Score:77.0%
Providers:5