> ## Documentation Index
> Fetch the complete documentation index at: https://docs.lyzr.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Google Models

> State-of-the-art multimodal models by Google, featuring massive context windows and advanced reasoning capabilities for the agentic era.

Google’s Gemini models are built for a native multimodal experience, allowing agents to process text, images, audio, and video simultaneously. These models are available to use without any additional configuration.

<AccordionGroup>
  <Accordion title="Gemini-3-pro-preview" defaultOpen={false}>
    Google's flagship reasoning-first model, optimized for complex autonomous agent workflows and frontier-level problem solving.

    **Use Cases:**

    * High-precision autonomous agents and planning
    * Advanced scientific research and PhD-level reasoning
    * Complex multimodal analytics (analyzing hours of video/audio)

    **Highlights:**

    * 1M+ token context window for deep information processing
    * Adaptive "Thinking" level for sophisticated logic
    * State-of-the-art performance in STEM and factual accuracy
  </Accordion>

  <Accordion title="Gemini-3-flash-preview" defaultOpen={false}>
    A high-speed frontier model that delivers Pro-grade intelligence with the latency and cost of a Flash model.

    **Use Cases:**

    * Real-time agentic coding and "vibe-coding" tasks
    * Scalable interactive data visualization
    * Responsive in-game assistants and live customer bots

    **Highlights:**

    * 3x faster than Gemini 2.5 Pro at a fraction of the cost
    * Exceptional tool-use and long-horizon task sequencing
    * Outperforms previous Pro models on SWE-bench coding evals
  </Accordion>

  <Accordion title="Gemini-2.5-pro" defaultOpen={false}>
    The high-capability thinking model designed for deep reasoning over vast datasets and complex codebases.

    **Use Cases:**

    * Analyzing entire code repositories or 1,000+ page documents
    * Multi-step technical and logical troubleshooting
    * Structured data extraction from messy, multimodal sources

    **Highlights:**

    * Features a 1M token context window (expandable to 2M)
    * Superior "Computer Use" capabilities for UI interaction
    * Highly stable performance for long-context RAG
  </Accordion>

  <Accordion title="Gemini-2.5-flash" defaultOpen={false}>
    The versatile, efficient workhorse of the 2.5 series, balancing speed with controllable reasoning.

    **Use Cases:**

    * High-volume document summarization and email triage
    * Agentic workflows requiring frequent, fast tool-calls
    * Real-time multimodal search and retrieval

    **Highlights:**

    * Controllable "Thinking Budget" to balance quality and latency
    * Native vision support for complex diagrams and charts
    * Excellent price-to-performance ratio for production scale
  </Accordion>

  <Accordion title="Gemini-2.5-flash-lite" defaultOpen={false}>
    An ultra-low latency model built for massive scale and high-throughput interactive applications.

    **Use Cases:**

    * Instant query resolution and simple chat UX
    * High-frequency classification and moderation
    * Lightweight embedded AI for mobile and web apps

    **Highlights:**

    * Optimized for maximum tokens-per-second
    * Maintains multimodal understanding at ultra-low cost
    * Ideal for tasks where speed is the absolute priority
  </Accordion>

  <Accordion title="Gemini-2.0-flash" defaultOpen={false}>
    A next-generation workhorse model designed specifically for the "agentic era" with built-in tool use.

    **Use Cases:**

    * General-purpose conversational agents
    * Real-time streaming applications via Multimodal Live API
    * Fast, cost-effective multimodal RAG pipelines

    **Highlights:**

    * 2x faster processing speed compared to Gemini 1.5 Pro
    * Native 1M token context window
    * Built-in support for grounding and parallel tool execution
  </Accordion>

  <Accordion title="Gemini-2.0-flash-lite" defaultOpen={false}>
    The most cost-effective entry point into the Gemini 2.0 ecosystem, streamlined for high-frequency tasks.

    **Use Cases:**

    * Simple Q\&A and sentiment analysis
    * Metadata generation for large image/video libraries
    * High-volume, low-complexity automation tasks

    **Highlights:**

    * Minimal computational resource requirements
    * Native multimodal input support (Text/Image/Video)
    * Industry-leading efficiency for basic inferencing needs
  </Accordion>
</AccordionGroup>

> 🌐 **Did you know?** Gemini models can process up to **1 hour of video** or **1 million tokens** in a single request, making them unrivaled for analyzing massive datasets in one go.