The problem of inaccurate floating point numbers is common in PHP, especially in financial calculations or precise comparisons. The root cause is that decimal decimals cannot be stored accurately in binary floating point representation (IEEE 754 standard), resulting in results such as 0.1 0.2 ≠ 0.3; 1. When comparing floating point numbers equality, use tolerance values (epsilon) instead of == directly; 2. Financial calculations should avoid using floating point numbers, and use integers (such as in units of division) or BCMath extensions; 3. BCMath performs arbitrary precision calculations through strings, which are suitable for high-precision scenarios, but have low performance; 4. It should be noted that PHP's type conversion may implicitly convert strings or integers into floating-point numbers to introduce errors; in short, floating-point numbers are inaccurate is a general calculation problem, but in PHP, it is more cautious because of loose types. In key scenarios, precise solutions such as integers or BCMath should be used. You should not rely on == to compare floating-point numbers, and you will never use floating-point numbers to deal with money.

Floating-point inaccuracies are a common source of confusion in PHP applications — especially when dealing with financial calculations, comparisons, or precision arithmetic. While PHP makes it easy to work with decimal numbers using float (also known as double ), developers often run into unexpected results like:

 var_dump(0.1 0.2 == 0.3); // bool(false)

This article breaks down why this happens and how to handle it properly in real-world PHP code.

Why Floating-Point Math Is Is Imprecise

The root cause lies in how computers represent decimal numbers in binary. Most decimal fractions (like 0.1 or 0.2) cannot be represented exactly in binary floating-point format, which is based on the IEEE 754 standard.

For example:

• 0.1 in binary is a repeating fraction (like 1/3 in decimal: 0.333…)
• So, PHP (like most languages) stores an approximation

This leads to tiny rounding errors that accumulate during calculations:

 echo 0.1 0.2; // 0.30000000000000000004

These inaccuracies are not bugs — they're inherent to floating-point arithmetic.

Common Scenarios Where This Causes Issues

1. Equality Comparisons

Direct equality checks fail due to tiny precision differences.

 if (0.1 0.2 == 0.3) {
    echo "Equal"; // This won't execute
}

? Fix: Use a tolerance (epsilon) for comparison

 function floatEqual($a, $b, $epsilon = 1e-10) {
    return abs($a - $b) < $epsilon;
}

var_dump(floatEqual(0.1 0.2, 0.3)); // true

2. Financial Calculations

Using floats for money can lead to off-by-penny errors.

 $price = 0.10;
$tax = 0.05;
$total = $price * (1 $tax); // Should be 0.105 → rounded to 0.11?
echo round($total, 2); // Might not always be accurate

? Fix: Work with integers (eg, cents), not dollars

 $cents = 100; // $1.00 → 100 cents
$taxPercent = 5;
$totalCents = $cents * (1 $taxPercent / 100); // 105 cents
echo $totalCents / 100; // 1.05

Alternatively, use strings and arbitrary precision libraries.

Use BCMath for Arbitrary Precision Arithmetic

PHP's BCMath extension allows precise decimal arithmetic using string-based numbers.

 // Add 0.1 0.2 accurately
$result = bcadd('0.1', '0.2', 2); // '0.30'
echo rtrim($result, '0'); // '0.3'

Other useful BCMath functions:

• bcsub() – subtraction
• bcmul() – multiplication
• bcdiv() – division
• All take an optional scale parameter (number of decimal places)

Example: Accurate multiplication

 $total = bcmul('0.1', '0.2', 3); // '0.020'

?? Note: BCMath requires numbers as strings and is slower than native floats, but essential for accuracy.

When to Use What?

Avoid floats for anything requiring exactly decimal representation — especially user-facing values like prices, quantities, or percentages.

Bonus: Watch Out for Type Juggling

PHP's loose typing can silently convert strings or integers to floats, reintroducing inaccuracies.

 $amount = "0.1";
$sum = $amount 0.2; // Now a float → imprecise

Always validate and sanitize numeric inputs, and consider casting to string before passing to BCMath.

Floating-point inaccuracies aren't unique to PHP — they're a universal computing limit. But in PHP applications, where type coercion is common and financial data often appears, the risks are higher.

The key is knowing when precision matters — and switching to safer alternatives like integer cents or BCMath when it does.

Basically: don't trust == with floats, and never use float for money.

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