33rd of 7 in ML frameworks and libraries
tensorflow
Tensor and neural network framework with Python and C++ APIs
Documentation ↗
(opens in a new tab)Website ↗
(opens in a new tab)Repository on GitHub ↗
(opens in a new tab)
- Stars
- 200.9k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- Mar 2026
- Language
- C++
Checked on GitHub.
Overview
TensorFlow is a machine learning framework for building, training and deploying models, with stable Python and C++ APIs and non-guaranteed APIs for other languages. It installs via pip, with CUDA GPU support on Ubuntu and Windows and a smaller CPU-only package. Related tooling includes TensorBoard and LiteRT for Android.
Who it is for: ML engineers and researchers building and deploying neural networks
Strengths
- Stable Python and C++ APIs
- CUDA GPU support via pip on Ubuntu and Windows; separate tensorflow-cpu package
- Device plugins for DirectX and macOS Metal
- Surrounding tooling: TensorBoard, LiteRT for Android, official models and tutorials
Weaknesses
- APIs for languages other than Python and C++ have no backward compatibility guarantee
- Built-in GPU support is CUDA only; other devices need separate plugins
- Linux XLA build artifacts listed as TBA
- RAM and VRAM requirements not stated in the README
What it needs
- GPU optional
- Needs Python, CUDA (for GPU)
- Models: LiteRT (Android)
Head to head
Also in ML frameworks and libraries
See all 7| Rank | Project | Score |
|---|---|---|
| 1 | transformersModel-definition library for text, vision, audio and multimodal models | 92 out of 100 |
| 2 | pytorchPython tensor library with GPU support and tape-based autograd for deep learning | 89 out of 100 |
| #4 | ultralyticsPython library and CLI for training and running YOLO vision models | 77 out of 100 |
| #5 | kerasMulti-backend deep learning library running on JAX, TensorFlow and PyTorch | 70 out of 100 |
| #6 | scikit-learnPython library of classical machine learning algorithms built on NumPy and SciPy | 69 out of 100 |