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Install TensorFlow for Java

TensorFlow provides a Java API— useful for loading models created with Python and running them within a Java application.

Nightly Libtensorflow Java packages

Libtensorflow JNI packages are built nightly and uploaded to GCS for all supported platforms. They are uploaded to the libtensorflow-nightly GCS bucket and are indexed by operating system and date built.

Supported Platforms

TensorFlow for Java is supported on the following systems:

  • Ubuntu 16.04 or higher; 64-bit, x86
  • macOS 10.12.6 (Sierra) or higher
  • Windows 7 or higher; 64-bit, x86

To use TensorFlow on Android see TensorFlow Lite

TensorFlow with Apache Maven

To use TensorFlow with Apache Maven, add the dependency to the project's pom.xml file:


GPU support

If your system has GPU support, add the following TensorFlow dependencies to the project's pom.xml file:


Example program

This example shows how to build an Apache Maven project with TensorFlow. First, add the TensorFlow dependency to the project's pom.xml file:

    <!-- The sample code requires at least JDK 1.7. -->
    <!-- The maven compiler plugin defaults to a lower version -->

Create the source file (src/main/java/HelloTensorFlow.java):

import org.tensorflow.Graph;
import org.tensorflow.Session;
import org.tensorflow.Tensor;
import org.tensorflow.TensorFlow;

public class HelloTensorFlow {
  public static void main(String[] args) throws Exception {
    try (Graph g = new Graph()) {
      final String value = "Hello from " + TensorFlow.version();

      // Construct the computation graph with a single operation, a constant
      // named "MyConst" with a value "value".
      try (Tensor t = Tensor.create(value.getBytes("UTF-8"))) {
        // The Java API doesn't yet include convenience functions for adding operations.
        g.opBuilder("Const", "MyConst").setAttr("dtype", t.dataType()).setAttr("value", t).build();

      // Execute the "MyConst" operation in a Session.
      try (Session s = new Session(g);
          // Generally, there may be multiple output tensors,
          // all of them must be closed to prevent resource leaks.
          Tensor output = s.runner().fetch("MyConst").run().get(0)) {
        System.out.println(new String(output.bytesValue(), "UTF-8"));

Compile and execute:

mvn -q compile exec:java  # Use -q to hide logging

The command outputs: Hello from version

TensorFlow with the JDK

TensorFlow can be used with the JDK through the Java Native Interface (JNI).


  1. Download the TensorFlow Jar Archive (JAR): libtensorflow.jar
  2. Download and extract the Java Native Interface (JNI) file for your operating system and processor support:
JNI versionURL
Linux CPU only https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-linux-x86_64-2.4.0.tar.gz
Linux GPU support https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-gpu-linux-x86_64-2.4.0.tar.gz
macOS CPU only https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-darwin-x86_64-2.4.0.tar.gz
Windows CPU only https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-2.4.0.zip
Windows GPU support https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-gpu-windows-x86_64-2.4.0.zip


Using the HelloTensorFlow.java file from the previous example, compile a program that uses TensorFlow. Make sure the libtensorflow.jar is accessible to your classpath:

javac -cp libtensorflow-2.4.0.jar HelloTensorFlow.java


To execute a TensorFlow Java program, the JVM must access libtensorflow.jar and the extracted JNI library.

Linux / macOS

java -cp libtensorflow-2.4.0.jar:. -Djava.library.path=./jni HelloTensorFlow


java -cp libtensorflow-2.4.0.jar;. -Djava.library.path=jni HelloTensorFlow

The command outputs: Hello from version

Build from source

TensorFlow is open source. Read the instructions to build TensorFlow's Java and native libraries from source code.