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DeepSeek-V2.5 vs Mistral NeMo Instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 12.4% higher average benchmark score. Mistral NeMo Instruct offers 239.6K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. 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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Mistral AI
Mistral Nemo was developed as a mid-sized instruction-tuned model, designed to balance capability with efficiency for practical deployments. Built to serve as a versatile foundation for various applications, it provides reliable performance across general language understanding and generation tasks.
2 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Mistral NeMo Instruct
Mistral AI
2024-07-18
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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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Mistral NeMo Instruct
Input:$0.15
Output:$0.15($0.12 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-V2.5
Average Score:80.4%(+12.4%)
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Mistral NeMo Instruct
Average Score:68.0%
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:80.4%(+12.4%)
Providers:3
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Mistral NeMo Instruct
Avg Score:68.0%
Providers:2