Gemini 3.5 Flash-Lite vs GPT-4.1 nano

Gemini 3.5 Flash-Lite is a natively multimodal reasoning model developed by Google DeepMind, released on July 21, 2026 as part of the Gemini 3.5 model family. It is the fastest model in the 3.5 series, designed for both low-latency tasks and high-throughput production workloads such as agentic search, document processing, receipt translation, and large-scale data extraction. The model accepts text, images, audio, and video as inputs, with a context window of up to 1 million tokens, and produces text output. It supports configurable thinking levels, allowing developers to tune the balance between response quality, cost, and latency depending on workload requirements.

31%), GDM-MRCR v2 long-context (72.2% vs. 60.1%), and real-world task execution as measured by GDPval-AA v2 (1140 vs. 642). 65.1%). According to the Artificial Analysis Index, the model generates output at approximately 350 tokens per second. It is built on the Gemini 3.5 Flash foundation and is evaluated across reasoning, coding, multimodal understanding, multilingual performance, and long-context tasks. The model is developed under Google's Frontier Safety Framework.

GPT-4.1 nano, released by OpenAI in April 2025, is the smallest and most cost-efficient member of the GPT-4.1 family. It is multimodal, supporting both text and image inputs, and retains the family’s extended 1 million-token context window—allowing it to handle large documents or codebases despite its lightweight design. Its training knowledge extends to June 2024.

GPT-4.1 nano prioritizes speed and affordability over raw reasoning power. While less capable than GPT-4.1 and GPT-4.1 mini, it is well-suited for high-volume or latency-sensitive workloads such as classification, autocomplete, content moderation, and lightweight assistants. This makes it an attractive option for developers seeking scalable deployment where efficiency is more critical than deep reasoning.