FIRE & early-retirement planning
Know your number.
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Completely. firenum runs entirely in your browser. Your numbers are saved only in your device's localStorage. There's no account, no cloud, and no server that stores your data, and nothing is ever sold or shared. Aggregate traffic stats use cookieless Cloudflare analytics. You can export everything to CSV or clear it at any time. See the privacy page for the full breakdown.
Your FIRE number is the total amount of money you need invested to cover your living expenses indefinitely without working. It's calculated by multiplying your annual expenses by 25 (based on the 4% safe withdrawal rate). For example, if you spend $40,000 per year, your FIRE number is $1,000,000.
Yes, as a starting point. The 4% rule is based on historical U.S. market data and has a 95% success rate over 30-year periods. However, it's not a guarantee. It's a guideline. For early retirees (40+ year retirements), consider using 3.5% for extra safety. The key is flexibility: if the market tanks early in your retirement, being willing to cut spending temporarily dramatically improves your odds.
The original Trinity study looked at 30-year periods. For longer retirements, you have options: use a more conservative 3-3.5% withdrawal rate (28-33x expenses), plan to earn some income in early retirement, or build in flexibility to reduce spending during market downturns. Historically, portfolios using the 4% rule often grew over 30 years rather than depleting, suggesting it works for longer periods too, but there are no guarantees.
Yes. All calculators support 9 currencies: USD ($), EUR (€), GBP (£), JPY (¥), CAD, AUD, CHF, INR (₹), and NZD. Use the currency selector in the navigation bar to switch. All calculations work the same regardless of currency. The math behind FIRE is universal. Your preference is saved automatically.
No account, no email, no sign-up. Every calculator, the Fire Planner, all simulations, and the guides are fully usable with nothing locked away or held back behind a paid tier.
Backtesting uses the Shiller S&P 500 monthly dataset, which runs from 1871 to the present. Monte Carlo simulations use a drift-corrected lognormal model calibrated to historical market volatility. The full methodology and sources are documented on the references page.