The difference in entropy coding matters more than most people realize, but it’s not about “file integrity” in the sense of corruption—it’s about how faithfully you can reconstruct the data with the least overhead. Gzip’s deflate uses Huffman coding after a fairly simple LZ77 pass. Zstd, on the other hand, does a richer LZ77 step and then uses a variant of RANS (Range Asymmetric Numeral System) for entropy, which is far more efficient at packing high‑entropy data. In practice, that means zstd can squeeze out a few extra percent of compression at the same speed or even faster on modern CPUs, because the entropy stage does not add as much latency as Huffman does. For integrity, both codecs are lossless, so as long as you’re not truncating the stream you’re fine. The trade‑off is really about how much CPU time you’re willing to spend on compression versus decompression, and how much bandwidth you can save. So if you’re looking for the fastest decompression on a device with limited CPU, gzip might win because its Huffman tables are very lightweight. If you need the absolute best compression ratio or you’re transmitting data over a bandwidth‑tight link, zstd’s entropy coding will give you a better return on your bandwidth investment. The choice boils down to speed vs. compression efficiency, not to data integrity.