Best Large Language Models for NotebookLM

Google AI Plus is a subscription plan that provides expanded access to Google’s advanced AI tools and Gemini-powered features for productivity, creativity, research, and everyday digital tasks. The plan includes enhanced usage limits for the Gemini app, access to video generation tools, Google Flow creative studio credits, Gemini integrations inside Google apps like Gmail and Docs, and expanded NotebookLM capabilities. Google AI Plus is designed to help users create content, conduct research, generate videos, manage workflows, and interact with AI-powered tools more efficiently through Google’s integrated AI ecosystem.

The Gemini Deep Research Agent is an autonomous research system that plans, searches, analyzes, and synthesizes multi-step findings using Gemini 3 Pro. Built for complex, long-running tasks, it performs iterative web searches, evaluates sources, and generates deeply structured, fully cited reports. Developers can run tasks asynchronously with background execution, enabling reliable long-duration workflows without timeouts. The agent also integrates with your own data through File Search, combining public web intelligence with private documents. Real-time streaming delivers progress, intermediate thoughts, and updates for transparent research. Designed for high-value analysis, the agent turns traditional research cycles into automated, repeatable, and scalable intelligence workflows.

Gemini Enterprise app is an advanced AI-powered platform that brings Google’s AI capabilities to every employee, enabling organizations to automate workflows, analyze data, and create high-quality content across multiple business functions. It securely connects to tools like Microsoft 365, Google Workspace, HubSpot, and Jira, allowing users to search and interact with their business data using natural language. The platform supports prebuilt agents such as NotebookLM and Deep Research, helping teams quickly extract insights and streamline tasks. It also allows users to build custom no-code agents to automate multi-step workflows across different applications. With centralized management, organizations can deploy and monitor all agents from a single interface. Built-in security and governance features ensure data privacy and compliance with enterprise standards. Overall, Gemini Enterprise app enhances productivity by combining AI automation with secure data integration.

Gemini 3.1 Pro is Google’s upgraded core intelligence model designed for complex tasks that require advanced reasoning. Building on the Gemini 3 series, it delivers significant improvements in problem-solving performance and logical pattern recognition. On the ARC-AGI-2 benchmark, Gemini 3.1 Pro achieved a verified score of 77.1%, more than doubling the reasoning performance of Gemini 3 Pro. The model is engineered for challenges where simple answers are insufficient, enabling deeper analysis, synthesis, and creative output. It can generate practical outputs such as animated, website-ready SVGs directly from text prompts, combining intelligence with real-world usability. Gemini 3.1 Pro is rolling out in preview across consumer, developer, and enterprise platforms including the Gemini app, NotebookLM, Gemini API, Gemini Enterprise Agent Platform, and Android Studio. With expanded access for Google AI Pro and Ultra users, 3.1 Pro sets a stronger baseline for agentic workflows.

Gemini 3.1 Flash-Lite is Google’s fastest and most cost-efficient model in the Gemini 3 series, designed for high-volume developer workloads. It delivers strong performance at scale while maintaining affordability, with pricing set at $0.25 per million input tokens and $1.50 per million output tokens. The model significantly improves speed, offering a 2.5x faster time to first answer token and a 45% increase in output speed compared to Gemini 2.5 Flash. Despite its lower cost tier, it achieves high benchmark results, including an Elo score of 1432 and strong performance across reasoning and multimodal evaluations. Gemini 3.1 Flash-Lite supports adaptive “thinking levels,” allowing developers to control how much reasoning power is used for different tasks. It is suitable for large-scale applications such as translation, content moderation, user interface generation, and simulation building.