Jev-Ultrafast: The Fastest and Cheapest Web Agent for High-Frequency Automation

Browser agents are fundamentally transforming how humans automate repetitive tasks across modern web interfaces. However, mainstream solutions suffer from slow decision loops and exorbitant token bills caused by repeatedly dumping multi-thousand-token DOM snapshots into frontier LLMs.

jev-ultrafast, developed jointly by browser-use and TypeSafe, changes the game completely. Surpassing 20,500+ Stars on GitHub with over 12,500+ Stars acquired in a single week, it is rapidly setting the new benchmark for browser automation.

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🚀 Instant Download via GH-Proxy

Access repository code, examples, and headless drivers without connection lag using GH-Proxy:

👉 Direct GH-Proxy Acceleration for Jev-Ultrafast
(Alternative URL: https://gh-proxy.com/https://github.com/browser-use/jev-ultrafast)

One-line installation:

git clone https://gh-proxy.com/https://github.com/browser-use/jev-ultrafast.git
cd jev-ultrafast
pip install -e .
playwright install chromium

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⚡ 7.1 Seconds for Real Flights Search

In public benchmarks, jev-ultrafast navigated Google Flights from a single natural-language instruction (“Search flights from Zürich to London next Friday”) to complete search results in just 7.1 seconds total—including live network latency and DOM rendering.

Dynamic Indexed Action Spaces

• Decoupled Action & Element Selection: Instead of forcing an LLM to generate unwieldy JSON schemas, TypeSafe’s Jev identifies the exact action (CLICK, SELECT, SCROLL) and target element index in a single forward pass.
• Selective Text Synthesis: A secondary lightweight LLM generates text strictly when the chosen action is TYPE_TEXT.

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🛠 Quick Start Code

import asyncio
from jev_ultrafast import BrowserAgent

async def run_task():
    agent = BrowserAgent(headless=False)
    output = await agent.run(
        goal="Go to Hacker News, locate the top story about AI, and return its link"
    )
    print("Target Link:", output)

asyncio.run(run_task())

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🎯 Impact & Use Cases

1. High-Frequency Testing & QA: Replace brittle Selenium/Cypress selectors with self-healing natural language agent flows.
2. Enterprise RPA Workflows: Execute cross-app form submissions and data reconciliations at 3x to 5x lower inference costs.
3. Resilient Data Scraping: Handle complex pagination, single-page application hydration, and multi-step filter forms effortlessly.