# DESILO's THOR Selected as Reference Implementation for Encrypted AI in Global FHE Benchmarking Suite

- Link: https://www.thailand-business-news.com/pr-news/desilos-thor-selected-as-reference-implementation-for-encrypted-ai-in-global-fhe-benchmarking-suite
- Published: 2026-07-29T07:36:00+07:00
- Author: PR Newswire

_— Establishing a universal benchmark for Private AI and encrypted Large Language
Model (LLM) inference_

SEOUL, South Korea, July 29, 2026 /PRNewswire/ — DESILO Inc. today announced that**
THOR** — the world’s first framework to run the entire LLM inference process directly
on encrypted data — has been officially added to the global FHE Benchmarking Suite
as the reference implementation for encrypted language-model inference. Through 
this, a common standard on which anyone can reproduce and compare the performance
of encrypted AI inference has been established, opening the door for enterprise 
in healthcare, finance, and the public sector to safely deploy powerful AI models
on sensitive data without risk of exposure.  

Fully homomorphic encryption (FHE) is a technology that enables model computation
directly on encrypted data without decryption, providing the strongest level of 
privacy protection in AI environments. Yet while technology has advanced dramatically,
results have been reported individually under differing hardware and parameter conditions,
making real progress difficult to assess objectively. The FHE Benchmarking Suite
is intended to resolve this by defining shared, reproducible workloads and performance
measures for the community. Within it, THOR is included as the first reference implementation
for encrypted language-model inference, serving as the reference point against which
related technologies can be compared and verified going forward.

"Homomorphic encryption has advanced quickly, but because measurement conditions
differ from one result to the next, systematic, objective comparison of real progress
has remained out of reach. Much like MLPerf in machine learning, the FHE Benchmarking
Suite serves as a reference point shared across the entire community," said Shruthi
Gorantala of Google, a co-lead of the FHE benchmarking suite. "With Transformer 
inference now included in the benchmark, encrypted inference is no longer a one-
off demonstration but a result anyone can reproduce, compare, and build on. That
is exactly how an ecosystem is formed."

THOR runs the widely used AI language model BERT with the data kept encrypted on
a single GPU, completing the benchmark inference workload while maintaining accuracy
on par with the unencrypted model (within about one percentage point). It processes
an existing open-source AI model end to end — from input through computation to 
output — entirely on encrypted data, without any separate retraining. Running an
entire LLM under encryption at a practical speed in this way is a world first for
THOR.

Performance highlights include:

 ◦ **Drastic Speed Improvement:** Inference time has been cut from about 10 minutes
   to about 2 minutes through continued optimization.
 ◦ **Matrix Acceleration:** Accelerates matrix multiplication — the core of the 
   computation — by up to 9.7 X over the previous state of the art, markedly improving
   processing speed long regarded as FHE’s greatest challenge.
 ◦ **Universal Standard:** THOR’s implementation and performance-measurement methodology
   in the suite can be reproduced and verified by anyone under the same conditions,
   serving as the baseline for comparing encrypted language-model inference technologies
   going forward.

"THOR’s inclusion in the FHE Benchmarking Suite reflects our belief that this field
should advance in the open, on shared standards; achievements must be verified, 
not merely asserted," said Seungmyung Lee, CEO of DESILO. "We are proud to present
the first implementation of a common foundation for encrypted language-model inference
and to release it as a common standard, and we will continue working to carry fully
homomorphic encryption from the research stage into real-world Private AI."

DESILO continues to advance FHE-based Private AI for enterprise and public-sector
use and participates in fully homomorphic encryption standardization discussions
at both the U.S. National Institute of Standards and Technology (NIST) and the International
Organization for Standardization (ISO).

**About DESILO**

DESILO Inc. is a leading deep-tech company dedicated to resolving the complex data-
privacy bottlenecks that arise in AI environments. Specializing in fully homomorphic
encryption (FHE) and advanced cryptographic frameworks, DESILO builds the core infrastructure
for a future of highly secure Private AI, enabling the global technology ecosystem
to draw full value from sensitive data without compromising security. DESILO is 
backed by leading investors including NAVER D2SF, Bon Angels Venture Partners, KB
Investment, Schmidt, SV Investment, the Korea Development Bank, and LG Electronics.

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