It really depends what you're using the floats for. For ML applications? 16 bit floats do the job with some trickery (quantization). For scientific computing?

It really depends what you're using the floats for. For ML applications? 16 bit floats do the job with some trickery (quantization). For scientific computing? Generally 64 bit floats give you the needed precision. But if you're chaining a lot of operations that exacerbate floating point error you may need more. For usage in trading? Again, depends on what computations you're doing. There's no "hard and fast" rule.