alt Hacker NewsTo throw out some real and up-to-date numbers from [1] for FHE at "128-bit security level", to sort 8x 8-bit unsigned integers on the most ordinary of desktop PCs, wait 3 seconds for the result. Want to sort 32x 8-bit unsigned integers instead? Come back 34 seconds later for the result.
update: also see [2] for some primitive unsigned 64-bit integer operation benchmarks with the TFHE-rs library (winner in the sorting performance comparison of [1]). Equality at 80ms, addition and subtraction at 100ms, division at 8 seconds, etc.
[1] https://eprint.iacr.org/2026/1495.pdf Oblivious Sorting under Fully Homomorphic Encryption: A Comprehensive Survey and Performance Analysis, Omar Ahmed and Rostin Shokri and Nektarios Georgios Tsoutsos, 2026
[2] https://docs.zama.org/tfhe-rs/tfhe-rs/1.0/get-started/benchm...
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That is sobering for sure, I wonder what the theoretical bounds are on what is possible if known. Would be such a dream to use a Frontier LLM one day with homomorphic encryption, but this sounds wildly implausible based on where things are today.
This seems a fine tradeoff to me, depending on the context. There are datasets and operations on them where speed being sacrificed for privacy/security seems appropriate.
Ideally, give me a dial, to ask for encrypted intelligence when I need it. Kind of like a private chat, but with deeper privacy protections.
Benchmarking code in repo: https://github.com/google/heir/tree/main/benchmark
Project intro talk from 2023: https://www.youtube.com/watch?v=kqDFdKUTNA4
It’s slightly better for LLMs because FHE is really bad at branches (it ends up essentially having to try both branches), making sorts nearly the worst possible thing to try since it’s all branches. In the case of AI most things are just addition and multiplication which can make some things faster since there aren’t as many branches. But we’re still nowhere near viability.