> ## 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.

# Groq Models

> Groq-hosted LLMs available in Lyzr with ultra-fast performance, ideal for real-time agent interactions

Groq is known for its **hardware-accelerated inferencing**, offering **blazing-fast response times** ideal for latency-sensitive applications. The models served through Groq in Lyzr come pre-integrated and require no additional setup.

<AccordionGroup>
  <Accordion title="LLaMA 3.3 70B Versatile" defaultOpen={false}>
    A state-of-the-art LLaMA model served on Groq’s hardware, optimized for general-purpose use with high speed.

    **Use Cases:**

    * High-speed chat agents
    * Real-time customer interaction bots
    * Lightweight RAG-based knowledge assistants

    **Highlights:**

    * Ultra-fast response time (token streaming in milliseconds)
    * Balanced accuracy and generation speed
    * Great for user-facing experiences
  </Accordion>

  <Accordion title="LLaMA 3.1 8B Instant" defaultOpen={false}>
    Smaller LLaMA model optimized for extremely lightweight and instant responses.

    **Use Cases:**

    * Instant query resolution
    * Embedded LLM features in apps
    * Low-cost multi-turn agents

    **Highlights:**

    * Minimal latency (ideal for mobile/web)
    * Lightweight for cost-effective scaling
    * Suitable for basic inferencing needs
  </Accordion>

  <Accordion title="LLaMA 4 Scout 17B (16E)" defaultOpen={false}>
    Meta's natively multimodal model using a Mixture-of-Experts (MoE) architecture, offering exceptional performance for its size.

    **Use Cases:**

    * Multimodal assistants (Text + Image reasoning)
    * High-speed coding and debugging tools
    * Multilingual chat support (12+ languages)

    **Highlights:**

    * Native vision support (early fusion architecture)
    * 128K context window for long-form analysis
    * Optimized for "assistant-like" conversational flow
  </Accordion>

  <Accordion title="LLaMA 4 Maverick 17B (128E)" defaultOpen={false}>
    The high-capacity variant of the LLaMA 4 series, featuring a massive 128-expert MoE architecture for deeper reasoning.

    **Use Cases:**

    * Complex decision-making and policy-based agents
    * Enterprise-scale orchestration
    * Knowledge-intensive research and reasoning

    **Highlights:**

    * Large-scale reasoning with 512K context support
    * Superior coding and technical problem-solving
    * Maintains sub-100ms latency on Groq hardware
  </Accordion>

  <Accordion title="GPT-oss-20B" defaultOpen={false}>
    An open-source GPT variant optimized for balanced performance and efficiency on Groq hardware.

    **Use Cases:** - General-purpose conversational agents

    * Fast inference for customer support and FAQs
    * Lightweight reasoning at scale

    **Highlights:** - Mid-sized open-source LLM

    * Optimized for Groq inferencing speed
    * Ideal for real-time interactive applications
  </Accordion>

  <Accordion title="GPT-oss-120B" defaultOpen={false}>
    A large-scale open-source model optimized for Groq, delivering deeper reasoning and broader coverage.

    **Use Cases:** - Knowledge-heavy assistants

    * Multi-turn conversational flows
    * Enterprise orchestration agents

    **Highlights:** - Large-scale reasoning capabilities

    * Supports complex queries with high accuracy
    * Extremely low latency for a 100B+ parameter model
  </Accordion>

  <Accordion title="Moonshot Kimi K2 Instruct" defaultOpen={false}>
    A frontier Mixture-of-Experts (MoE) model designed for autonomous agentic intelligence.

    **Use Cases:**

    * Autonomous agents requiring tool-calling
    * Complex multi-step reasoning tasks
    * Interactive data visualization and frontend coding

    **Highlights:**

    * 256K context window for long-horizon tasks
    * State-of-the-art "Agentic" reasoning and tool-use
    * High-tier performance in math and technical logic
  </Accordion>
</AccordionGroup>

> ⚡ With Groq, agents in Lyzr get **sub-100ms latency** inferencing, making it ideal for real-time apps where user experience and responsiveness are critical.