AI Platform Prediction uses container images, based on runtime version designation, to configure cloud resources to service your training and prediction requests. This page lists the runtime versions and their constituent packages. For more information, see Managing runtime versions .
Supported AI Platform Prediction runtime versions
The following versions are supported in AI Platform Prediction:
scikit-learn 1.0.2
XGBoost 1.6.2
GPUs are supported for online prediction in this runtime version.
Runtime version 2.11 does not support batch prediction .
Python 3.7 is the only version of Python available for online prediction with runtime version 2.11. You cannot use Python 2 with runtime version 2.11.
Starting on January 27, 2024 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On January 27, 2025 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 1.0.2
XGBoost 1.6.1
GPUs are supported for online prediction in this runtime version.
Runtime version 2.10 does not support batch prediction .
Python 3.7 is the only version of Python available for online prediction with runtime version 2.10. You cannot use Python 2 with runtime version 2.10.
Starting on November 02, 2023 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On November 02, 2024 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 1.0.2
XGBoost 1.6.1
GPUs are supported for online prediction in this runtime version.
Runtime version 2.9 does not support batch prediction .
Python 3.7 is the only version of Python available for online prediction with runtime version 2.9. You cannot use Python 2 with runtime version 2.9.
Starting on August 30, 2023 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On August 30, 2024 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 1.0
XGBoost 1.5.1
GPUs are supported for online prediction in this runtime version.
Runtime version 2.8 does not support batch prediction .
Python 3.7 is the only version of Python available for online prediction with runtime version 2.8. You cannot use Python 2 with runtime version 2.8.
Starting on March 16, 2023 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On March 16, 2024 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 1.0
XGBoost 1.4.2
GPUs are supported for online prediction in this runtime version.
Runtime version 2.7 does not support batch prediction .
Python 3.7 is the only version of Python available for online prediction with runtime version 2.7. You cannot use Python 2 with runtime version 2.7.
Starting on November 17, 2022 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On November 17, 2023 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.24.2
XGBoost 1.4.2
GPUs are supported for online prediction in this runtime version.
Runtime version 2.6 does not support batch prediction .
Python 3.7 is the only version of Python available for online prediction with runtime version 2.6. You cannot use Python 2 with runtime version 2.6.
Starting on October 6, 2022 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On October 6, 2023 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.24.1
XGBoost 1.4.0
GPUs are supported for training and online prediction in this runtime version.
Runtime version 2.5 does not support batch prediction .
Python 3.7 is the only version of Python available for online prediction with runtime version 2.5. You cannot use Python 2 with runtime version 2.5.
Starting on August 13, 2022 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On August 13, 2023 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.24.0
XGBoost 1.3.1
GPUs are supported for training and online prediction in this runtime version.
Runtime version 2.4 does not support batch prediction .
Python 3.7 is the only version of Python available for training and online prediction with runtime version 2.4. You cannot use Python 2 with runtime version 2.4.
Starting on April 16, 2022 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On April 16, 2023 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.23.2
XGBoost 1.2.1
GPUs are supported for training and online prediction in this runtime version.
Runtime version 2.3 does not support batch prediction .
Python 3.7 is the only version of Python available for training and online prediction with runtime version 2.3. You cannot use Python 2 with runtime version 2.3.
Starting on December 9, 2021 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On December 9, 2022 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.23.1
XGBoost 1.1.1
GPUs are supported for training and online prediction in this runtime version.
Runtime version 2.2 does not support batch prediction .
Python 3.7 is the only version of Python available for training and online prediction with runtime version 2.2. You cannot use Python 2 with runtime version 2.2.
Starting on August 28, 2021 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On August 28, 2022 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.22.1
XGBoost 0.90
Runtime version 2.1 supports TensorFlow 2.1.0 for CPU and GPU. GPUs are supported for training and online prediction in this runtime version.
Python 3.7 is the only version of Python available for training and online prediction with runtime version 2.1. You cannot use Python 2 with runtime version 2.1.
Starting on March 9, 2021 , you can no longer create training jobs that use this runtime version or model versions that use this runtime version. Batch Prediction will continue to be supported.
On January 31, 2023 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.20.4
XGBoost 0.82
Runtime version 1.15 supports TensorFlow 1.15.0 for CPU and GPU. GPUs are supported for training and online prediction in this runtime version.
Python 3.7 is available for training and online prediction with runtime version 1.15. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on September 30, 2022 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On September 30, 2023 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.20.2
XGBoost 0.81
Runtime version 1.14 supports TensorFlow 1.14.0 for CPU and GPU. GPUs are supported for training and online prediction in this runtime version.
Python 3.5 is available for training and online prediction with runtime version 1.14. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on July 19, 2020 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On July 19, 2021 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.20.2
XGBoost 0.81
Runtime version 1.13 supports TensorFlow 1.13.1 for CPU and GPU. GPUs are supported for training and online prediction in this runtime version.
Python 3.5 is available for training and online prediction with runtime version 1.13. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on July 19, 2020 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On March 6, 2021 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.20.0
XGBoost 0.81
Runtime version 1.12 supports TensorFlow 1.12.3 for CPU and GPU. GPUs are supported for training and online prediction in this runtime version.
Python 3.5 is available for training and online prediction with runtime version 1.12. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on July 19, 2020 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On December 19, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.19.2
XGBoost 0.80
Runtime version 1.11 supports TensorFlow 1.11.0 for CPU and GPU. GPUs are supported for training and online prediction in this runtime version.
Python 3.5 is available for training and online prediction with runtime version 1.11. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on July 19, 2020 , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On December 19, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.19.2
XGBoost 0.72.1
Runtime version 1.10 supports TensorFlow 1.10.0 for CPU and GPU (GPUs are not supported for online prediction).
Python 3.5 is available for training and online prediction with runtime version 1.10. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on (date not set) , you can no longer create training jobs, batch prediction jobs, or model versions that use this runtime version.
On August 31, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.19.1
XGBoost 0.72.1
Runtime version 1.9 supports TensorFlow 1.9.0 for CPU and GPU (GPUs are not supported for online prediction).
Python 3.5 is available for training and online prediction with runtime version 1.9. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on March 16, 2020 , you can no longer create training jobs that use this runtime version.
Starting on (date not set) , you can no longer create batch prediction jobs or model versions that use this runtime version.
On June 27, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.19.1
XGBoost 0.71
Runtime version 1.8 supports TensorFlow 1.8.0 for CPU and GPU (GPUs are not supported for online prediction).
Python 3.5 is available for training and online prediction with runtime version 1.8. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
The gcloud
and google-cloud-logging
packages
have been replaced with the google-cloud
package, which
contains both of the removed packages.
Starting on March 16, 2020 , you can no longer create training jobs that use this runtime version.
Starting on (date not set) , you can no longer create batch prediction jobs or model versions that use this runtime version.
On May 8, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.19.1
XGBoost 0.7.post3
Runtime version 1.7 supports TensorFlow 1.7.0 for CPU and GPU.
Python 3.5 is available for training and online prediction with runtime version 1.7. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on March 16, 2020 , you can no longer create training jobs that use this runtime version.
Starting on (date not set) , you can no longer create batch prediction jobs or model versions that use this runtime version.
On April 26, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.19.1
XGBoost 0.7.post3
Runtime version 1.6 supports TensorFlow 1.6.0 for CPU and GPU.
Python 3.5 is available for training and online prediction with runtime version 1.6. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on March 16, 2020 , you can no longer create training jobs that use this runtime version.
Starting on (date not set) , you can no longer create batch prediction jobs or model versions that use this runtime version.
On April 13, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.19.1
XGBoost 0.7.post3
Runtime version 1.5 supports TensorFlow 1.5.0 for CPU and GPU.
Python 3.5 is available for training and online prediction with runtime version 1.5. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
Starting on March 16, 2020 , you can no longer create training jobs that use this runtime version.
Starting on (date not set) , you can no longer create batch prediction jobs or model versions that use this runtime version.
On April 13, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
scikit-learn 0.18.1
XGBoost 0.6a2
Runtime version 1.4 uses TensorFlow 1.4.0 for online prediction, and 1.4.1 for batch prediction and training.
Python 3.5 is available for training and online prediction with runtime version 1.4. The Ubuntu packages for Python 3 (indicated in bold ) are installed when running Python 3.
The earliest AI Platform Prediction runtime version that provides support for scikit-learn and XGBoost is version 1.4.
Starting on March 16, 2020 , you can no longer create training jobs that use this runtime version.
Starting on (date not set) , you can no longer create batch prediction jobs or model versions that use this runtime version.
On April 13, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
Runtime version 1.2 uses an Ubuntu 16.04 OS base image instead of the Debian Jessie version used by 1.0.
Starting on March 16, 2020 , you can no longer create training jobs that use this runtime version.
Starting on (date not set) , you can no longer create batch prediction jobs or model versions that use this runtime version.
On April 13, 2020 , AI Platform Prediction deletes all your model versions that use this runtime version.
Policy for supporting older runtime versions
AI Platform Training and AI Platform Prediction support each runtime version for one year after its release date.
Support for each runtime version changes according to the following schedule:
-
Starting on the release date:You can create training jobs, batch prediction jobs, and model versions that use the runtime version.
-
Starting 12 months after the release date:You can no longer create training jobs, batch prediction jobs, or model versions that use the runtime version.
Existing model versions that have been deployed to AI Platform Prediction continue to function.
-
Starting 24 months after the release date:AI Platform Prediction automatically deletes all model versions that use the runtime version.
A modified version of this policy is being applied retroactively, over several stages, to runtime versions 1.13 and earlier. Refer to this document for the current availability of each runtime version.
Support for GPUs
GPU-enabled machines come pre-installed with tensorflow-gpu , the TensorFlow Python package with GPU support.
Other machines come pre-installed with the regular tensorflow package instead.
Support for AI Explanations
AI Platform Prediction runtime version(s) 1.15, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10, and 2.11 are available for prediction and explanation requests with AI Explanations. See how to request explanations .