GPT-4.1 nano vs Qwen2.5-VL 32B 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-VL-32B-Instruct is a 32-billion-parameter vision-language model from Alibaba, extending the Qwen2.5 architecture with multimodal capabilities for understanding images, documents, charts, and video frames alongside text. The model was designed for tasks requiring deep visual reasoning — such as document parsing, table extraction, and spatial understanding — with performance that made it a practical choice for document intelligence and visual data analysis workflows. As an open-weight model, it became a widely adopted foundation for fine-tuning domain-specific multimodal applications.