Google Gemini 2.0 vs. LearnLM 1.5 Pro

This document compares Google's Gemini 2.0 and LearnLM 1.5 Pro models based on the provided search results.

Gemini 2.0

Source: Introducing Gemini 2.0: our new AI model for the agentic era

Key Features:

• More capable than previous versions: Features native image and audio output and tool use.
• Gemini 2.0 Flash: Available to developers and trusted testers, with wider availability planned for early next year. Outperforms Gemini 1.5 Pro on key benchmarks at twice the speed. Supports multimodal inputs (images, video, audio) and outputs (natively generated images, text-to-speech audio). Natively calls tools like Google Search and code execution.
• Agentic Experiences: Google is exploring agentic experiences with Gemini 2.0, including Project Astra, Project Mariner, and Jules (see below for details).
• Responsible AI Development: Google emphasizes responsible AI development, prioritizing safety and security.

Gemini 2.0 Flash Model Details (from Google AI for Developers):

Source: Gemini models | Gemini API | Google AI for Developers

Property	Description
Model code	models/gemini-2.0-flash-exp
Supported data types (Inputs)	Audio, images, video, and text
Supported data types (Output)	Text, images (coming soon), and audio (coming soon)
Token limits (Input)	1,048,576
Token limits (Output)	8,192
Rate limits	10 RPM, 4 million TPM, 1,500 RPD
Capabilities	Structured outputs (Supported), Caching (Not supported), Tuning (Not supported), Function calling (Supported), Code execution (Supported), Search (Supported), Image generation (Supported), Native tool use (Supported), Audio generation (Supported)

LearnLM 1.5 Pro

Source: LearnLM | Gemini API | Google AI for Developers

LearnLM is an experimental, task-specific model trained to align with learning science principles for teaching and learning.

Key Capabilities:

• Inspiring active learning: Allows for practice and healthy struggle with timely feedback.
• Managing cognitive load: Presents relevant, well-structured information in multiple modalities.
• Adapting to the learner: Dynamically adjusts to goals and needs, grounding in relevant materials.
• Stimulating curiosity: Inspires engagement to provide motivation.
• Deepening metacognition: Helps the learner plan, monitor, and reflect on progress.

LearnLM is an experimental model available in AI Studio. The provided documentation includes example system instructions and user prompts demonstrating its capabilities in test preparation, teaching concepts, releveling text for different grade levels, guiding students through learning activities, and providing homework help. These examples highlight LearnLM's focus on interactive and adaptive learning experiences.

Note: The Reddit links provided contain broken images and are inaccessible, preventing further analysis of the comparison discussions.