siboehm/lleaves
Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.
This project helps data scientists and machine learning engineers significantly speed up predictions from their LightGBM models. You provide a trained LightGBM model, and it outputs an optimized version that makes predictions much faster, whether for individual requests or large batches of data. It's designed for those who need low-latency or high-throughput model inference.
463 stars. Available on PyPI.
Use this if you have LightGBM models in production and need to reduce their prediction time by a factor of 10 or more.
Not ideal if your application's performance is not bottlenecked by LightGBM model inference speed or if you are not using LightGBM models.
Stars
463
Forks
43
Language
Python
License
MIT
Category
Last pushed
Jan 01, 2026
Commits (30d)
0
Dependencies
2
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