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Mistral Small 3.1 24B Base vs o4-mini
Comprehensive side-by-side LLM comparison
o4-mini leads with 33.1% higher average benchmark score. o4-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. Overall, o4-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
o4-mini was created as part of the next generation of OpenAI's reasoning models, designed to continue advancing the balance between analytical capability and operational efficiency. Built to bring cutting-edge reasoning techniques to applications requiring quick turnaround, it represents the evolution of compact reasoning-focused models.
1 month newer
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
o4-mini
OpenAI
2025-04-16
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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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o4-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:48.4%
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o4-mini
Average Score:81.5%(+33.1%)
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Knowledge Cutoff
Training data recency comparison
o4-mini
2024-05-31
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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o4-mini
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Mistral Small 3.1 24B Base
Avg Score:48.4%
Providers:1
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o4-mini
Avg Score:81.5%(+33.1%)
Providers:1