In the case of flushing subnormals to zero, it's easy to end up with divides by zero when it wouldn't otherwise. `0/0.0` is `NaN` but `0/subnormal` is `Inf`.

In the case of flushing subnormals to zero, it's easy to end up with divides by zero when it wouldn't otherwise. `0/0.0` is `NaN` but `0/subnormal` is `Inf`. In other cases, `-ffast-math` just introduces arbitrary and strange behaviors. Sometimes you end up with higher precision than you expected. Other times you end up with less. Other times it'll helpfully just re-arrange things such that it's a zero. For example, the classical Kahan summation does the following: t = sum + y c = (t - sum) - y https://en.wikipedia.org/wiki/Kahan_summation_algorithm https://en.wikipedia.org/wiki/Kahan_summation_algorithm A -ffast-math compiler will see that — algebraically — you can just substitute `sum + y` into the equation for `c` and get 0. It's `sum + y - sum - y`. And that's true for real maths. But it's not true for floating point numbers. It explicitly destroys any attempt at _working with_ floating point numbers.