---
title: Scoring Code overview
description: How to use the Scoring Code feature for qualifying Leaderboard models, allowing you to use DataRobot-generated models outside of the DataRobot platform.

---

# Scoring Code overview {: #scoring-code-overview }

!!! info "Availability information"
     Contact your DataRobot representative for information on enabling the Scoring Code feature.

Scoring Code allows you to export DataRobot-generated models as JAR files that you can use outside of the platform. DataRobot automatically runs code generation for qualifying models and indicates code availability with a SCORING CODE [indicator](leaderboard-ref#tags-and-indicators) on the Leaderboard.

You can export a model's Scoring Code from the [Leaderboard](sc-download-leaderboard) or [the model's deployment](sc-download-deployment). The download includes a pre-compiled JAR file (with all dependencies included), as well as the source code JAR file. Once exported, you can view the model's source code to help understand each step DataRobot takes in producing your predictions.

Scoring Code JARs contain Java Scoring Code for a predictive model. The prediction calculation logic is identical to the DataRobot API&mdash;the code generation mechanism tests each model for accuracy as part of the generation process. The generated code is easily deployable in any environment and is not dependent on the DataRobot application.

??? tip "How does DataRobot determine which models will have Scoring Code?"
    When the Scoring Code feature is enabled, DataRobot generates a Java alternative for each blueprint preprocessing step and compares its results on the validation set with the original results. If the difference between results is greater than 0.00001, DataRobot does not provide the option to download the Scoring Code. In this way, DataRobot ensures that the Scoring Code JAR model always produces the same predictions as the original model. If verification fails, check the [**Log**](log) tab for error details.

## Why use Scoring Code? {: #why-use-scoring-code }

* **Flexibility**: Can be used anywhere that Java code can be executed.

* **Speed**: Provides low-latency scoring without the API call overhead. Java code is typically faster than scoring through the Python API.

* **Integrations**: Lets you integrate models into systems that can’t necessarily communicate with the DataRobot API. The Scoring Code can be used either as a primary means of scoring for fully offline systems or as a backend for systems that are using the DataRobot API.

* **Precision**: Provides a complete match of predictions generated by DataRobot and the JAR model.

* **Hardware**: Allows you to use additional hardware to score large amounts of data.

See the following sections for more details:

* Downloading Scoring Code from the [Leaderboard](sc-download-leaderboard) or [a deployment](sc-download-deployment)
* [Scoring at the command line](scoring-cli)
* [JAR file structure](jar-package)
* [Scoring Code JAR integrations](sc-jar-integrations)

!!! note
    The model JAR files require Java 8 or later.

{% include 'includes/scoring-code-consider.md' %}
