Model Comparison

GPT-4.1 nano vs Magistral Small 2506

Magistral Small 2506 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GPT-4.1 nano outperforms in 0 benchmarks, while Magistral Small 2506 is better at 2 benchmarks (AIME 2024, GPQA).

Magistral Small 2506 significantly outperforms across most benchmarks.

Fri May 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only GPT-4.1 nano specifies input context (1,047,576 tokens). Only GPT-4.1 nano specifies output context (32,768 tokens).

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Mistral AI
Magistral Small 2506
Input- tokens
Output- tokens
Fri May 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4.1 nano supports multimodal inputs, whereas Magistral Small 2506 does not.

GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4.1 nano

Text
Images
Audio
Video

Magistral Small 2506

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while Magistral Small 2506 uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

GPT-4.1 nano

Proprietary

Closed source

Magistral Small 2506

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while Magistral Small 2506 was released on 2025-06-10.

Magistral Small 2506 is 2 months newer than GPT-4.1 nano.

GPT-4.1 nano

Apr 14, 2025

1.1 years ago

Magistral Small 2506

Jun 10, 2025

11 months ago

1mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a knowledge cutoff of 2024-05-31, while Magistral Small 2506 has a cutoff of 2025-06-01.

Magistral Small 2506 has more recent training data (up to 2025-06-01), making it potentially better informed about events through that date compared to GPT-4.1 nano (2024-05-31).

GPT-4.1 nano

May 2024

Magistral Small 2506

Jun 2025

1.1 yr newer

Outputs Comparison

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Key Takeaways

OpenAI
Larger context window (1,047,576 tokens)
Supports multimodal inputs
Mistral AI
Has open weights
Higher AIME 2024 score (70.7% vs 29.4%)
Higher GPQA score (68.2% vs 50.3%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4.1 nano
Mistral AI
Magistral Small 2506

FAQ

Common questions about GPT-4.1 nano vs Magistral Small 2506.

Which is better, GPT-4.1 nano or Magistral Small 2506?

Magistral Small 2506 significantly outperforms across most benchmarks. GPT-4.1 nano is made by OpenAI and Magistral Small 2506 is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT-4.1 nano compare to Magistral Small 2506 in benchmarks?

GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Magistral Small 2506 scores AIME 2024: 70.7%, GPQA: 68.2%, AIME 2025: 62.8%, LiveCodeBench: 51.3%.

What are the context window sizes for GPT-4.1 nano and Magistral Small 2506?

GPT-4.1 nano supports 1.0M tokens and Magistral Small 2506 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4.1 nano and Magistral Small 2506?

Key differences include multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4.1 nano and Magistral Small 2506?

GPT-4.1 nano is developed by OpenAI and Magistral Small 2506 is developed by Mistral AI.