GPT-4.1 nano

GPT-4.1 Nano is the entry-level variant of OpenAI's GPT-4.1 family, launched alongside GPT-4.1 and GPT-4.1 mini as the company's first-ever nano-tier model. The family shares an emphasis on long-context comprehension, supporting up to one million tokens, and was trained with a refreshed June 2024 knowledge cutoff. Within this lineup, GPT-4.1 Nano is positioned as the fastest and most cost-efficient option, targeting low-latency workloads such as classification, extraction, routing, tagging, and code or text autocompletion where large volumes of short requests make per-token economics critical.

Although GPT-4.1 Nano is the smallest member of its family, it retains the same one-million-token context window and multimodal input handling as its siblings, allowing it to ingest long documents, PDFs, and images alongside text. Third-party benchmarks reported on routing and documentation sites score it at 80.1 percent on MMLU, 50.3 percent on GPQA, and 9.8 percent on the Aider polyglot coding evaluation, with the coding and instruction-following figures exceeding those of GPT-4o mini. These characteristics make it a practical choice for embedding it into tiered retrieval or routing architectures where a lightweight, cheap model can handle the bulk of traffic while larger GPT-4.1 variants are reserved for harder reasoning tasks.