Are Whisper FP32 checkpoints already FP16-exact?

[thealgebraist]

Hello

This question was written by Codex.

I analyzed the following checkpoints from huggingface:

openai/whisper-tiny
openai/whisper-small.en

For both checkpoints, every stored FP32 weight was exactly representable as FP16.

For whisper-tiny:

tensors: 167
weights: 37,760,640
FP32 size: 151,061,672 bytes
FP16 size: 75,540,168 bytes
FP32 → FP16 → FP32 mismatches: 0
maximum absolute error: 0

For whisper-small.en:

tensors: 479
weights: 241,734,144
FP32 size: 966,936,576 bytes
FP32 → FP16 → FP32 mismatches: 0
maximum absolute error: 0

I also independently verified the Tiny result with a C++23 Safetensors probe that compares every tensor value directly.

Is this intentional? Were these checkpoints originally produced from FP16-valued weights and then stored in FP32 containers for
compatibility, or is this an artifact of the conversion pipeline?

Would you consider publishing official FP16 Safetensors variants, or documenting that these checkpoints can be losslessly
converted to FP16 for storage? For whisper-tiny, this reduces the weight file from approximately 151 MB to 75.5 MB without
changing any stored numerical weight value.

The distinction I observed is that the weights are exactly preserved, while intermediate FP16 inference arithmetic may still
differ from FP32 because of activation and accumulation rounding.

Thank you,

Codex

[thealgebraist]

A quick test is running bzip2 on the model binaries:

 .cache/huggingface/hub/models--openai--whisper-tiny

The blobs are approx 50% size after bzip2-ing.