Model Comparison

Codestral-22B vs GPT-4.1 nano

Comparing Codestral-22B and GPT-4.1 nano across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and GPT-4.1 nano don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

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).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Sat May 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4.1 nano supports multimodal inputs, whereas Codestral-22B does not.

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

Codestral-22B

Text
Images
Audio
Video

GPT-4.1 nano

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while GPT-4.1 nano uses a proprietary license.

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

Codestral-22B

MNPL-0.1

Open weights

GPT-4.1 nano

Proprietary

Closed source

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while GPT-4.1 nano was released on 2025-04-14.

GPT-4.1 nano is 11 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.0 years ago

GPT-4.1 nano

Apr 14, 2025

1.1 years ago

10mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Codestral-22B's cutoff date is not specified.

We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without Codestral-22B's cutoff date.

Codestral-22B

—

GPT-4.1 nano

May 2024

Outputs Comparison

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Key Takeaways

Mistral AI
Has open weights
OpenAI
Larger context window (1,047,576 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
OpenAI
GPT-4.1 nano

FAQ

Common questions about Codestral-22B vs GPT-4.1 nano.

Which is better, Codestral-22B or GPT-4.1 nano?

Codestral-22B (Mistral AI) and GPT-4.1 nano (OpenAI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Codestral-22B compare to GPT-4.1 nano in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%.

What are the context window sizes for Codestral-22B and GPT-4.1 nano?

Codestral-22B supports an unknown number of tokens and GPT-4.1 nano supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Codestral-22B and GPT-4.1 nano?

Key differences include multimodal support (no vs yes), licensing (MNPL-0.1 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and GPT-4.1 nano?

Codestral-22B is developed by Mistral AI and GPT-4.1 nano is developed by OpenAI.