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Mistral Small 3.1 24B Base vs o3-mini
Comprehensive side-by-side LLM comparison
o3-mini leads with 22.8% higher average benchmark score. o3-mini offers 44.0K more tokens in context window than Mistral Small 3.1 24B Base. Mistral Small 3.1 24B Base is $5.10 cheaper per million tokens. Mistral Small 3.1 24B Base supports multimodal inputs. Overall, o3-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
o3-mini was created as an efficient variant of the o3 reasoning model, designed to provide advanced thinking capabilities with reduced computational requirements. Built to make next-generation reasoning accessible to a broader range of applications, it balances analytical depth with practical speed and cost considerations.
1 month newer
o3-mini
OpenAI
2025-01-30
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($5.10 cheaper)
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o3-mini
Input:$1.10
Output:$4.40
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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o3-mini
Average Score:82.0%(+22.8%)
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Knowledge Cutoff
Training data recency comparison
o3-mini
2023-09-30
More recent knowledge cutoff means awareness of newer technologies and frameworks
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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o3-mini
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Mistral Small 3.1 24B Base
Avg Score:59.3%
Providers:1
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o3-mini
Avg Score:82.0%(+22.8%)
Providers:2