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Mistral Small 3 24B Instruct vs Phi 4
Comprehensive side-by-side LLM comparison
Mistral Small 3 24B Instruct leads with 1.6% higher average benchmark score. Mistral Small 3 24B Instruct offers 32.0K more tokens in context window than Phi 4. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Mistral Small 24B Instruct was created as the instruction-tuned version of the 24B base model, designed to follow user instructions reliably. Built to serve general-purpose applications requiring moderate capability, it balances performance with deployment practicality.
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Microsoft
Phi-4 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
1 month newer
Phi 4
Microsoft
2024-12-12
Mistral Small 3 24B Instruct
Mistral AI
2025-01-30
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Pricing Comparison
Cost per million tokens (USD)
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Mistral Small 3 24B Instruct
Input:$0.07
Output:$0.14
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Phi 4
Input:$0.07
Output:$0.14
Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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Mistral Small 3 24B Instruct
Average Score:72.9%(+1.6%)
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Phi 4
Average Score:71.3%
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Knowledge Cutoff
Training data recency comparison
Mistral Small 3 24B Instruct
2023-10-01
Phi 4
2024-06-01
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 24B Instruct
2 providers
DeepInfra
Throughput: 49 tok/s
Latency: 0.2ms
Mistral AI
Throughput: 134 tok/s
Latency: 0.2ms
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Mistral Small 3 24B Instruct
Avg Score:72.9%(+1.6%)
Providers:2
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Phi 4
Avg Score:71.3%
Providers:1