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DeepSeek-V2.5 vs Mistral Small 3.1 24B Base
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Mistral Small 3.1 24B Base offers 239.6K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. Mistral Small 3.1 24B Base supports multimodal inputs. DeepSeek-V2.5 is available on 3 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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Mistral AI
Mistral Small 3.1 24B Base represents an updated iteration of the 24B foundation model, developed with architectural refinements and improved training. Built to provide enhanced base capabilities for fine-tuning, it incorporates learnings from previous versions for better downstream performance.
10 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
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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 Small 3.1 24B Base
Input:$0.10
Output:$0.30($0.02 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%
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Mistral Small 3.1 24B Base
Average Score:81.0%(+0.6%)
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%
Providers:3
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Mistral Small 3.1 24B Base
Avg Score:81.0%(+0.6%)
Providers:1