Comprehensive side-by-side LLM comparison
GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Mistral AI
Codestral is a 22-billion-parameter code-specialized model from Mistral AI, released in May 2024 as the company's first dedicated coding model, trained with focus on fill-in-the-middle (FIM) completion, code generation, and repair across 80+ programming languages. Unlike Mistral's general-purpose Apache 2.0 models, Codestral was released under a separate non-production research license, reflecting its positioning as a professional coding tool requiring commercial API access for production deployment. Its FIM support made it particularly valued for IDE integrations and code completion tools that need to insert code within existing contexts rather than only appending to the end.
OpenAI
GPT-4.1 nano is OpenAI's smallest member of the GPT-4.1 family, released in April 2025 alongside GPT-4.1 and GPT-4.1 mini as the latency-optimized, cost-minimized option for high-throughput applications. Positioned below GPT-4.1 mini in both size and cost, it was designed for use cases where speed and affordability dominate over raw capability — including tool calling, intent classification, short-form instruction following, and retrieval-augmented lookup tasks. Unlike its larger siblings, it supports fine-tuning, making it a practical candidate for task-specific customization at scale without incurring the cost of fine-tuning larger models.
10 months newer

Codestral 22B
Mistral AI
2024-05-29

GPT-4.1 nano
OpenAI
2025-04-14
Context window and performance specifications
GPT-4.1 nano
2024-06
Available providers and their performance metrics
Codestral 22B
GPT-4.1 nano
OpenAI
Codestral 22B
GPT-4.1 nano
Codestral 22B
GPT-4.1 nano