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Mistral Small vs Phi 4
Comprehensive side-by-side LLM comparison
Mistral Small offers 33.5K more tokens in context window than Phi 4. Phi 4 is $0.59 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Mistral Small was created as an efficient model offering, designed to provide capable language understanding with reduced computational requirements. Built to serve cost-sensitive applications while maintaining quality, it enables Mistral's technology in scenarios where resource efficiency is valued.
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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.
2 months newer
Mistral Small
Mistral AI
2024-09-17
Phi 4
Microsoft
2024-12-12
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Pricing Comparison
Cost per million tokens (USD)
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Mistral Small
Input:$0.20
Output:$0.60
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Phi 4
Input:$0.07
Output:$0.14($0.59 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
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
1 providers
Mistral AI
Throughput: 0.1 tok/s
Latency: 0.5ms
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Phi 4
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Mistral Small
Avg Score:0.0%
Providers:1
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Phi 4
Avg Score:0.0%
Providers:1