GPT-4.1 nano vs Qwen2.5 14B Instruct

GPT-4.1 nano

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.

Alibaba / Qwen

Qwen2.5-14B-Instruct is a 14-billion-parameter language model from Alibaba released in September 2024 within the Qwen2.5 family, occupying the mid-tier of the series between efficiency-focused small models and the high-capability 72B flagship. Trained on 18 trillion tokens with emphasis on instruction alignment, code understanding, and multilingual reasoning, it offers a strong performance-to-compute ratio for developers who need more capability than 7B but cannot serve 32B or larger models. The model supports 128K context windows and structured output generation out of the box.