Paper 2025/2318 Original: eprint.iacr.org/2025/2318 ↗

Hyperion: Private Token Sampling with Homomorphic Encryption

Lawrence Lim
Jiaming Liu
Vikas Kalagi
Divyakant Agrawal
Amr El Abbadi
Abstract

A promising direction for enabling private queries to large language models (LLMs) is with homomorphic encryption (HE). An open problem is performing token sampling under HE. In this paper, we introduce Hyperion, an efficient HE algorithm for inverse transform sampling, enabling private token sampling with 1 comparison depth, $O(1)$ amortized comparisons, and $O(\log n)$ rotations. We implement our approach and demonstrate that it samples tokens in 0.14 seconds for 32k tokens ($\approx 4.4\, \mu\mathrm{s}$ per token) on GPU, achieving a $100\times$ latency improvement over prior work.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Preprint.
History
2026-07-03: last updated
2025-12-23: published
Short URL
https://ia.cr/2025/2318
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2025/2318,
      author = {Lawrence Lim and Jiaming Liu and Vikas Kalagi and Divyakant Agrawal and Amr El Abbadi},
      title = {Hyperion: Private Token Sampling with Homomorphic Encryption},
      howpublished = {Cryptology {ePrint} Archive, Paper 2025/2318},
      year = {2025},
      url = {https://eprint.iacr.org/2025/2318}
}
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