We just open-sourced tritify — Pelloran’s deterministic AI inference runtime built around exact integer arithmetic.

The core idea is simple:

Same weights. Same input. Same execution schedule. Same bits.

Why this matters

Typical optimized floating-point inference is not bit-identical across environments by default.

Different hardware, compiler behavior, reduction order, threading, or math libraries can change the low-order bits of a result.

For many workloads, that is acceptable.

But if you want AI inference to be independently reproducible and verifiable, “almost the same” is not the same as “the same.”

tritify takes a different approach.

Its runtime inference path uses fully specified integer arithmetic so that the output can be reproduced exactly across supported environments.

What we tested

In our experiments, tritify demonstrated:

bit-identical inference across tested CPU architectures

deterministic integer execution with a floating-point reference for verification

reproducible…