xgboost-cpu

What it is and what it does

XGBoost-cpu is a CPU-only variant of the XGBoost gradient boosting library, stripped of GPU acceleration and federated learning support to minimize installation size. It's built for environments where disk or memory constraints make the full XGBoost package impractical, while retaining the core gradient boosting algorithm for classification, regression, and ranking tasks.

The package depends only on numpy and scipy, making it relatively lightweight. It ships as pre-built wheels for x86_64 Linux and Windows platforms only; users on other architectures or seeking GPU support should install the standard xgboost package instead. The library is actively maintained, supports modern Python versions (3.12+), and carries an Apache-2.0 license.

Use it for:

• Train gradient boosting models in containerized or resource-limited environments where full XGBoost would exceed storage budgets.
• Build CPU-based ML pipelines on x86_64 Linux or Windows servers without GPU infrastructure.
• Develop and test XGBoost models locally before deploying to GPU-accelerated production systems.
• Use XGBoost in embedded or edge deployments where GPU support is unnecessary or unavailable.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

XGBoost CPU-only gradient boosting library for machine learning model training and prediction without GPU acceleration, designed for space-constrained environments.

Yes, if you need XGBoost on x86_64 Linux or Windows and have storage or memory constraints. The active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. No if you require GPU acceleration, federated learning, or run on non-x86_64 platforms—use the standard xgboost package instead.

Install

xgboost-cpu on PyPI

pip install xgboost-cpu

uv add xgboost-cpu

poetry add xgboost-cpu

Installing xgboost-cpu

Before you install

Medium install friction due to platform-specific wheels (x86_64 Linux and Windows only); active maintenance with a release 10 days ago and 28654 repository stars. Requires Python 3.12 or later.

License in practice

Apache-2.0 permissive license allows commercial and private use with minimal restrictions.

Quickstart

pip install xgboost-cpu

import xgboost as xgb
model = xgb.XGBClassifier()
model.fit(X_train, y_train)

Platform support limited to x86_64 Linux and Windows; other platforms require the standard xgboost package. Requires Python 3.12 or later.

Verify before relying

• Whether performance characteristics differ meaningfully from the standard xgboost package on CPU workloads.
• Compatibility with popular ML frameworks (scikit-learn, pandas pipelines) beyond basic numpy/scipy integration.
• Whether the space savings justify the platform limitation for typical use cases.

Package facts

Evidence: xgboost_cpu-3.4.0-py3-none-manylinux_2_28_aarch64.whl; xgboost_cpu-3.4.0-py3-none-manylinux_2_28_x86_64.whl; xgboost_cpu-3.4.0-py3-none-win_amd64.whl; xgboost_cpu-3.4.0-py3-none-win_arm64.whl

Tags

More Artificial Intelligence packages