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Devstral Small 1.1 vs Phi 4
Comprehensive side-by-side LLM comparison
Devstral Small 1.1 offers 224.0K 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
Devstral Small was developed as a more efficient development-focused model, designed to bring software engineering assistance to resource-conscious deployments. Built to provide coding capabilities with reduced computational requirements, it enables developer tools in environments where efficiency is paramount.
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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.
7 months newer
Phi 4
Microsoft
2024-12-12
Devstral Small 1.1
Mistral AI
2025-07-11
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Pricing Comparison
Cost per million tokens (USD)
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Devstral Small 1.1
Input:$0.10
Output:$0.30
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Phi 4
Input:$0.07
Output:$0.14($0.19 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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Devstral Small 1.1
1 providers
Mistral AI
Throughput: 137.1 tok/s
Latency: 0.23ms
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Phi 4
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Devstral Small 1.1
Avg Score:0.0%
Providers:1
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Phi 4
Avg Score:0.0%
Providers:1