Gemini 3.1 Flash-Lite

Gemini 3.1 Flash-Lite 介绍

Gemini 3.1 Flash-Lite is Google's most cost-efficient AI model in the Gemini 3 series, designed for high-volume workloads with best-in-class intelligence. It offers exceptional speed, low token pricing, and competitive performance on reasoning and multimodal benchmarks, making it ideal for scalable AI tasks. This model balances affordability with accuracy, featuring adjustable Thinking Levels for enhanced reasoning without significant delays.

核心功能

Low cost at $0.25 per million input tokens and $1.50 per million output tokens

High speed with 2.5X faster first token and 45% higher output speed compared to Gemini 2.5 Flash

Adjustable Thinking Levels for improved reasoning accuracy without heavy lag

Strong performance on benchmarks like GPQA Diamond and MMMU Pro, surpassing prior generations

典型使用场景

Developers integrating AI APIs for fast and cost-effective applications such as chatbots or data processors

Startups handling high-volume tasks like email summarization, code snippet fixing, or real-time translation

Businesses extracting and analyzing key information from large text datasets or documents efficiently

为什么适合初创团队

Startups need Gemini 3.1 Flash-Lite because it provides a cost-effective and scalable AI solution, allowing them to integrate high-performance features without straining budgets. Its fast response times and efficient processing support rapid development and deployment, essential for agility and growth in competitive markets.

常见问题

What is the pricing for Gemini 3.1 Flash-Lite?

The pricing is $0.25 per million tokens for input and $1.50 per million tokens for output, making it highly affordable for high-volume usage.

How does Gemini 3.1 Flash-Lite compare to other models like Gemini 2.5 Flash?

It outperforms Gemini 2.5 Flash with 2.5X faster first token time and 45% higher output speed, while matching or exceeding quality on various benchmarks.

What tasks is Gemini 3.1 Flash-Lite best suited for?

It is optimized for high-throughput tasks such as summarization, code fixing, translation, and data extraction, where speed and cost-efficiency are critical.

Does Gemini 3.1 Flash-Lite support multimodal inputs?

Yes, it performs well on multimodal understanding benchmarks, indicating capability with diverse data types like text and images.

Gemini 3.1 Flash-Lite