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Devstral Small 1.1 vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
GPT-4.1 nano offers 824.3K more tokens in context window than Devstral Small 1.1. Both models have similar pricing. GPT-4.1 nano supports multimodal inputs. 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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OpenAI
GPT-4.1 Nano was developed as the smallest and most efficient variant in the GPT-4.1 family, designed for applications requiring minimal latency and resource usage. Built to enable AI capabilities on edge devices and resource-constrained environments, it distills GPT-4.1 capabilities into an ultra-compact form factor.
2 months newer
GPT-4.1 nano
OpenAI
2025-04-14
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($0.10 cheaper)
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GPT-4.1 nano
Input:$0.10
Output:$0.40
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
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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Devstral Small 1.1
1 providers
Mistral AI
Throughput: 137.1 tok/s
Latency: 0.23ms
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GPT-4.1 nano
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Devstral Small 1.1
Avg Score:0.0%
Providers:1
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GPT-4.1 nano
Avg Score:0.0%
Providers:1