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GPT-4.1 nano vs Pixtral Large
Comprehensive side-by-side LLM comparison
Pixtral Large leads with 10.9% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Pixtral Large. GPT-4.1 nano is $7.50 cheaper per million tokens. Overall, Pixtral Large is the stronger choice for coding tasks.
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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.
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Mistral AI
Pixtral Large was developed as a larger-scale multimodal model, designed to provide advanced vision-language understanding capabilities. Built to handle complex tasks requiring sophisticated analysis of visual and textual information, it represents Mistral's flagship offering for multimodal applications.
4 months newer
Pixtral Large
Mistral AI
2024-11-18
GPT-4.1 nano
OpenAI
2025-04-14
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Pricing Comparison
Cost per million tokens (USD)
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GPT-4.1 nano
Input:$0.10
Output:$0.40($7.50 cheaper)
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Pixtral Large
Input:$2.00
Output:$6.00
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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GPT-4.1 nano
Average Score:55.8%
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Pixtral Large
Average Score:66.7%(+10.9%)
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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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GPT-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
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Pixtral Large
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GPT-4.1 nano
Avg Score:55.8%
Providers:1
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Pixtral Large
Avg Score:66.7%(+10.9%)
Providers:1