xgboost-node
Run XGBoost models and make predictions directly in Node.js.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is xgboost-node?
xgboost-node allows developers to integrate XGBoost machine learning models into their Node.js applications, enabling seamless prediction capabilities within the JavaScript ecosystem.
Key differentiator
“xgboost-node stands out by providing a direct integration of XGBoost models into Node.js, allowing developers to leverage powerful machine learning capabilities within their JavaScript applications without the need for external services or platforms.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Official documentation lacks comprehensive guides on advanced model tuning and deployment scenarios
Running XGBoost models within a JavaScript runtime can introduce latency compared to native Python execution
Fit analysis
Who is it for?
✓ Best for
Node.js developers who need to integrate XGBoost models directly into their applications without external dependencies.
Projects requiring efficient and fast model execution within the Node.js runtime.
✕ Not a fit for
Developers looking for a cloud-based service for machine learning predictions
Teams that require real-time streaming data processing with complex ML models
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Works well with
Next step
Get Started with xgboost-node
Step-by-step setup guide with code examples and common gotchas.