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DeepSeek-V3 vs Mistral Small 3.1 24B Base
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 16.3% higher average benchmark score. DeepSeek-V3 offers 6.1K more tokens in context window than Mistral Small 3.1 24B Base. Mistral Small 3.1 24B Base is $0.97 cheaper per million tokens. Mistral Small 3.1 24B Base supports multimodal inputs. Overall, DeepSeek-V3 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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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.
2 months newer
DeepSeek-V3
DeepSeek
2024-12-25
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-V3
Input:$0.27
Output:$1.10
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Mistral Small 3.1 24B Base
Input:$0.10
Output:$0.30($0.97 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-V3
Average Score:74.5%(+16.3%)
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Mistral Small 3.1 24B Base
Average Score:58.2%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Mistral Small 3.1 24B Base
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DeepSeek-V3
Avg Score:74.5%(+16.3%)
Providers:1
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Mistral Small 3.1 24B Base
Avg Score:58.2%
Providers:1