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GPT-4.1 nano vs Magistral Small 2506
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 22.3% higher average benchmark score. GPT-4.1 nano supports multimodal inputs. Overall, GPT-4.1 nano is the stronger choice for coding tasks.
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OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
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Mistral AI
Magistral Small 2506 is a language model developed by Mistral AI. It achieves strong performance with an average score of 63.2% across 4 benchmarks. Notable strengths include AIME 2024 (70.7%), GPQA (68.2%), AIME 2025 (62.8%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Mistral AI's latest advancement in AI technology.
1 month newer
GPT-4.1 nano
OpenAI
2025-04-14
Magistral Small 2506
Mistral AI
2025-06-10
Performance Metrics
Context window and performance specifications
Average performance across 27 common benchmarks
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GPT-4.1 nano
Average Score:31.6%(+22.3%)
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Magistral Small 2506
Average Score:9.4%
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
Magistral Small 2506
2025-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GPT-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
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Magistral Small 2506
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GPT-4.1 nano
Avg Score:31.6%(+22.3%)
Providers:1
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Magistral Small 2506
Avg Score:9.4%
Providers:0