TensorFlow

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Freedom report

Three barsScore 6.7

Free tierA free tier is on its own pricing page
Open codeNo open-source code on record
Runs widely6 of 6 device platforms
DocumentedPlans, terms and facts published

TensorFlow is a platform for building machine-learning models and deploying them across servers, edge devices, and the web. Its model-building options include the Keras API, eager execution, and distributed training. For production workflows, TFX supports pipelines, TensorFlow Lite targets mobile and edge inference, and TensorFlow.js supports JavaScript environments, including browsers and Node.js. The broader ecosystem includes tf.data, TensorFlow Datasets, TensorBoard, and LiteRT. TensorFlow also provides tools and resources for fairness, interpretability, privacy, and security, including TF Privacy and TF Federated. It supports Python, Java, Go, and JavaScript, with model formats including SavedModel, Keras .keras, TensorFlow Lite, and TensorFlow.js. The platform is free and open source under the Apache 2.0 license. Supported 64-bit systems include Ubuntu, Windows, and macOS; macOS has no GPU support, and WSL2 GPU support is experimental. Google Colab can run TensorFlow tutorials in browser-based Jupyter notebooks without local setup.

Who it is for

TensorFlow suits developers and teams building machine-learning models for varied deployment environments, including server, edge, web, and mobile use. It also fits those looking for distributed training or responsible-AI resources.

What is good

Free and open source under Apache 2.0.
Supports distributed training.
Deploys to servers, edge devices, and web.
Works with Python, Java, Go, and JavaScript.
Offers privacy tools for training and federated learning.

What to know first

macOS has no GPU support.
WSL2 GPU support is marked experimental.

Verdict

TensorFlow provides a free platform spanning model development and deployment across multiple environments. Check the system support details if GPU acceleration on macOS or WSL2 is important to your workflow.

TensorFlow plans and pricing

All plans

TensorFlow Free Open-source machine learning platform · installable packages for supported systems tensorflow.org · 29 Sept 2026

Compared on deep learning software

Free plan: Yes
Training mode: local
Deployment targets: multiple
GPU acceleration: Yes
Distributed training: Yes
Supported languages: Python, Java, Go, JavaScript
Model formats: SavedModel, Keras .keras, TensorFlow Lite (.tflite), TensorFlow.js

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The record

Product: TensorFlow is an end-to-end platform for creating machine learning models that can run in different environments.
Model building: TensorFlow offers the high-level Keras API, eager execution, and a Distribution Strategy API for distributed training.
Production deployment: TensorFlow supports model deployment on servers, edge devices, and the web, with TFX for production pipelines, TensorFlow Lite for mobile and edge inference, and TensorFlow.js for JavaScript environments.
Ecosystem: The TensorFlow ecosystem includes TensorFlow.js, LiteRT, tf.data, TFX, tf.keras, TensorFlow Datasets, and TensorBoard.
Integrations: The TFX pipeline tutorial describes exporting pipeline source code that can be orchestrated with Apache Airflow and Apache Beam.
Responsible AI: TensorFlow provides resources and tools addressing fairness, interpretability, privacy, and security in machine learning workflows.
Privacy tools: The responsible AI toolkit lists TF Privacy for training models with privacy and TF Federated for federated learning.
Supported systems: The install guide lists tested and supported 64-bit environments including Ubuntu, Windows, and macOS, plus WSL2 with GPU support marked experimental.
Platform limitation: The install guide states that macOS has no GPU support for TensorFlow.
Browser development: TensorFlow.js is described as a JavaScript library for training and deploying machine learning models in the browser, Node.js, mobile, and other environments.
Cloud learning option: Google Colab runs TensorFlow tutorials in a browser-based Jupyter notebook environment with no installation or setup required.
Support: TensorFlow directs users to its issue tracker, release notes, Stack Overflow, community forum, and announcement mailing list.
License and release: TensorFlow's API and reference implementation were released as an open-source package under the Apache 2.0 license in November 2015.
Maker: TensorFlow's whitepaper describes the system as built at Google.
Price from: Free

Where it ranks on Freedom251

Best Deep Learning Software in 2026#4 of 36

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Sources

tensorflow.org· checked 29 Sept 2026
tensorflow.org/about· checked 29 Sept 2026
tensorflow.org/tfx/tutorials/tfx/components_keras· checked 29 Sept 2026
tensorflow.org/responsible_ai· checked 29 Sept 2026
tensorflow.org/install· checked 29 Sept 2026
tensorflow.org/community· checked 29 Sept 2026
tensorflow.org/about/bib· checked 29 Sept 2026