> ## Documentation Index > Fetch the complete documentation index at: https://docs.browser-use.com/llms.txt > Use this file to discover all available pages before exploring further. # Fast Agent > Optimize agent performance for maximum speed and efficiency. ```python theme={null} import asyncio from dotenv import load_dotenv load_dotenv() from browser_use import Agent, BrowserProfile # Speed optimization instructions for the model SPEED_OPTIMIZATION_PROMPT = """ Speed optimization instructions: - Be extremely concise and direct in your responses - Get to the goal as quickly as possible - Use multi-action sequences whenever possible to reduce steps """ async def main(): # 1. Use fast LLM - Llama 4 on Groq for ultra-fast inference from browser_use import ChatGroq llm = ChatGroq( model='meta-llama/llama-4-maverick-17b-128e-instruct', temperature=0.0, ) # from browser_use import ChatGoogle # llm = ChatGoogle(model='gemini-flash-lite-latest') # 2. Create speed-optimized browser profile browser_profile = BrowserProfile( minimum_wait_page_load_time=0.1, wait_between_actions=0.1, headless=False, ) # 3. Define a speed-focused task task = """ 1. Go to reddit https://www.reddit.com/search/?q=browser+agent&type=communities 2. Click directly on the first 5 communities to open each in new tabs 3. Find out what the latest post is about, and switch directly to the next tab 4. Return the latest post summary for each page """ # 4. Create agent with all speed optimizations agent = Agent( task=task, llm=llm, flash_mode=True, # Disables thinking in the LLM output for maximum speed browser_profile=browser_profile, extend_system_message=SPEED_OPTIMIZATION_PROMPT, ) await agent.run() if __name__ == '__main__': asyncio.run(main()) ``` ## Speed Optimization Techniques ### 1. Fast LLM Models ```python theme={null} # Groq - Ultra-fast inference from browser_use import ChatGroq llm = ChatGroq(model='meta-llama/llama-4-maverick-17b-128e-instruct') # Google Gemini Flash - Optimized for speed from browser_use import ChatGoogle llm = ChatGoogle(model='gemini-flash-lite-latest') ``` ### 2. Browser Optimizations ```python theme={null} browser_profile = BrowserProfile( minimum_wait_page_load_time=0.1, # Reduce wait time wait_between_actions=0.1, # Faster action execution headless=True, # No GUI overhead ) ``` ### 3. Agent Optimizations ```python theme={null} agent = Agent( task=task, llm=llm, flash_mode=True, # Skip LLM thinking process extend_system_message=SPEED_PROMPT, # Optimize LLM behavior ) ```