Install & Compatibility
Where this runs
tested against v2.22.0.dev20260302 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.940 runs
build_error
glibcpy 3.10–3.940 runs
installs and imports cleanly · install 45.0s · import 10.317s · 2252.8MB
2294MB installed
● package 2294MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
tensorflow
✓ import tensorflow as tf
This quickstart verifies the installation of TensorFlow Nightly, prints its version, performs a basic tensor operation, and checks for available GPU devices.
import tensorflow as tf
# Verify TensorFlow Nightly installation and basic functionality
print("TensorFlow version:", tf.__version__)
# Perform a simple operation
hello = tf.constant('Hello, TensorFlow Nightly!')
print(hello.numpy().decode('utf-8'))
# Example of tensor operation
result = tf.add(tf.constant(1), tf.constant(2))
print(f"1 + 2 = {result.numpy()}")
# Check for GPU devices (if applicable)
gpus = tf.config.list_physical_devices('GPU')
if gpus:
print(f"GPU devices found: {len(gpus)}")
for gpu in gpus:
print(f" {gpu}")
else:
print("No GPU devices found.")
tensorflow --version
Debug
Known issues
breakingtf-nightly is built from the HEAD of the development branch and may contain API changes, incomplete features, or bugs that are not present in stable TensorFlow releases. Compatibility is not guaranteed between daily builds.fixUse a stable TensorFlow release (`tensorflow`) for production or environments requiring high stability. If using `tf-nightly`, frequently update your code and be prepared for potential breaking changes. Pin exact nightly versions for reproducible builds if necessary.
affects: All tf-nightly versions
gotchaInstalling `tf-nightly` alongside `tensorflow` in the same Python environment can lead to conflicts, unexpected behavior, and broken installations due to overlapping package contents.fixAlways install `tf-nightly` in a clean, isolated virtual environment (e.g., using `venv` or `conda`) separate from any stable TensorFlow installations.
affects: All versions
deprecatedThe `tf-nightly-gpu` package has been deprecated since TensorFlow 2.12 (early 2023) and is no longer being published. GPU support is now included directly in the main `tf-nightly` package.fixUse `pip install tf-nightly` for GPU-enabled builds. The separate `tf-nightly-gpu` package is no longer necessary or maintained.
affects: tf-nightly >= 2.12.0.dev*
gotchaNightly builds receive minimal testing compared to stable releases, meaning they are more prone to undiscovered bugs and regressions.fixOnly use `tf-nightly` for early access to new features, testing, or contributing to TensorFlow development. Avoid using it in critical production systems where stability and predictability are paramount.
affects: All tf-nightly versions
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Version history
2.22.0.dev20260531latest on PyPI · released May 31, 2026
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Dependencies
No dependency data recorded yet.