FP8 (E4M3 and E5M2)
Beginner
Two 8-bit number formats used for AI: one keeps a little more detail, the other a little more range.
Novice
8-bit floating point, standardized by the Open Compute Project. E4M3 has 4 exponent and 3 mantissa bits (largest value 448); E5M2 has 5 and 2 (largest 57,344). Each tensor usually gets its own scale factor so its values land in range.
Expert
OCP OFP8: E4M3 (bias 7, no infinities, single NaN pattern, 18 binades) for weights and activations; E5M2 (bias 15, IEEE-style specials, 32 binades) for gradients. Used with per-tensor or finer scaling, saturating conversion and higher-precision accumulation.
Explained in Number formats (Architectures).
See also: Scale factor, Microscaling (MX).