Comprehensive side-by-side LLM comparison
GPT-4.1 nano offers 879.6K more tokens in context window than MiniMax M2.1. GPT-4.1 nano is $0.80 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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.
MiniMax
MiniMax M2.1, released by MiniMax on December 23, 2025, is a large language model with approximately 230 billion parameters featuring strong multi-language programming capabilities and an industry-leading multilingual coding profile. It features a 196K token context window and is optimized for complex real-world software engineering tasks across Rust, Java, Golang, C++, TypeScript, and other languages. M2.1 targets agentic coding workflows and applications requiring production-grade programming across diverse language environments.
8 months newer

GPT-4.1 nano
OpenAI
2025-04-14
MiniMax M2.1
MiniMax
2025-12-23
Cost per million tokens (USD)
GPT-4.1 nano
MiniMax M2.1
Context window and performance specifications
GPT-4.1 nano
2024-06
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
MiniMax M2.1
GPT-4.1 nano
MiniMax M2.1
GPT-4.1 nano
MiniMax M2.1
MiniMax