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Compound Beta Mini

Preview
compound-beta-mini
Try it in Playground
TOKEN SPEED
~350 tps
Powered bygroq
INPUT
Text
OUTPUT
Text
CAPABILITIES
Web Search, Code Execution, JSON Object Mode
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Compound beta mini is a compound AI system powered by an openly available model already supported in GroqCloud to intelligently and selectively use tools to answer user queries, starting first with web search and code execution.

PRICING

Varies. Pricing is based on input/output tokens to underlying models (while in preview)

LIMITS

CONTEXT WINDOW
131,072
MAX OUTPUT TOKENS
8,192

QUANTIZATION

This uses Groq's TruePoint Numerics, which reduces precision only in areas that don't affect accuracy, preserving quality while delivering significant speedup over traditional approaches. Learn more here.

Key Technical Specifications

Model Architecture

Compound-beta-mini leverages Llama 4 Scout for core reasoning along with Llama 3.3 70B to help with routing and tool use. Unlike compound-beta, it can only use one tool per request, but has an average of 3x lower latency.

Performance Metrics

Groq developed a new evaluation benchmark for measuring search capabilities called RealtimeEval. This benchmark is designed to evaluate tool-using systems on current events and live data. On the benchmark, Compound Beta Mini outperformed GPT-4o-search-preview and GPT-4o-mini-search-preview significantly.
Learn More About Agentic Tooling
Discover how to build powerful applications with real-time web search and code execution

Use Cases

Realtime Web Search

Automatically access up-to-date information from the web using the built-in web search tool.

Code Execution

Execute Python code automatically using the code execution tool powered by E2B.

Code Generation and Technical Tasks
Create AI tools for code generation, debugging, and technical problem-solving with high-quality multilingual support.

Best Practices

  • Use system prompts to improve steerability and reduce false refusals. Compound-beta-mini is designed to be highly steerable with appropriate system prompts.
  • Consider implementing system-level protections like Llama Guard for input filtering and response validation.
  • Deploy with appropriate safeguards when working in specialized domains or with critical content.
  • Compound-beta-mini should not be used by customers for processing protected health information. It is not a HIPAA Covered Cloud Service under Groq's Business Associate Addendum for customers at this time.

Quick Start

Experience the capabilities of compound-beta-mini on Groq:

shell
pip install groq
Python
from groq import Groq
client = Groq()
completion = client.chat.completions.create(
    model="compound-beta-mini",
    messages=[
        {
            "role": "user",
            "content": "Explain why fast inference is critical for reasoning models"
        }
    ]
)
print(completion.choices[0].message.content)

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