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Mistral Small 3.1 24B Base vs o1-mini
Comprehensive side-by-side LLM comparison
o1-mini leads with 13.3% higher average benchmark score. Mistral Small 3.1 24B Base offers 62.5K more tokens in context window than o1-mini. Mistral Small 3.1 24B Base is $14.60 cheaper per million tokens. Mistral Small 3.1 24B Base supports multimodal inputs. Overall, o1-mini is the stronger choice for coding 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.
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OpenAI
o1-mini was created as a faster, more cost-effective reasoning model, designed to bring extended thinking capabilities to applications with tighter latency and budget constraints. Built to excel particularly in coding and STEM reasoning while maintaining affordability, it provides a more accessible entry point to reasoning-enhanced AI assistance.
6 months newer
o1-mini
OpenAI
2024-09-12
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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Mistral Small 3.1 24B Base
Input:$0.10
Output:$0.30($14.60 cheaper)
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o1-mini
Input:$3.00
Output:$12.00
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:59.3%
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o1-mini
Average Score:72.6%(+13.3%)
Provider Availability & Performance
Available providers and their performance metrics
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Mistral Small 3.1 24B Base
1 providers
Mistral AI
Throughput: 137.1 tok/s
Latency: 0.23ms
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o1-mini
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Mistral Small 3.1 24B Base
Avg Score:59.3%
Providers:1
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o1-mini
Avg Score:72.6%(+13.3%)
Providers:2