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Mistral Small 3.1 24B Base vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Mistral Small 3.1 24B Base leads with 9.2% higher average benchmark score. Both models have similar pricing. Mistral Small 3.1 24B Base supports multimodal inputs. Overall, Mistral Small 3.1 24B Base 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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Microsoft
Phi-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
6 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
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
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($0.20 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:58.2%(+9.2%)
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Phi-3.5-mini-instruct
Average Score:48.9%
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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Phi-3.5-mini-instruct
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Mistral Small 3.1 24B Base
Avg Score:58.2%(+9.2%)
Providers:1
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Phi-3.5-mini-instruct
Avg Score:48.9%
Providers:1