tf-nightly-cpu
TensorFlow is an open source machine learning framework for everyone.
Decision gist · record as of 2026-08-14
Yes, if you need the latest TensorFlow development features and have a CPU-only environment or prefer not to manage GPU drivers. No, if you require production stability—use a stable TensorFlow release instead. The nightly build is actively maintained and carries no known vulnerabilities, but development snapshots are inherently less tested than stable versions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.10; CPU-only build will not use GPU acceleration even if CUDA is present.
- Medium install friction due to 20 runtime dependencies including numpy, keras-nightly, protobuf, and grpcio.
- Active maintenance with releases every few days; latest commit 2026-08-14.
License · maintenance · safety
Apache 2.0 (permissive) — Apache 2.0 permissive license allows commercial and private use with minimal restrictions, though you must include a copy of the license and note any modifications to the library itself.
last release 2026-08-09 (5 days) · last repo commit 2026-08-14 · 197,024 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 257,516 downloads/mo, #8,444 on PyPI
Alternatives
Verify before relying
pip install tf-nightly-cpu
import tf_nightly_cpu- Whether nightly builds receive the same security review and stability guarantees as stable releases.
- Performance characteristics and numerical accuracy differences between nightly and stable versions.
- Compatibility matrix for specific hardware accelerators beyond the CUDA 12 classifiers listed.
What it is and what it does
tf-nightly-cpu is a nightly development snapshot of TensorFlow compiled for CPU-only execution. It includes the full TensorFlow API for numerical computation and machine learning across a wide range of domains. The package bundles 20 core dependencies—including numpy for array operations, keras-nightly for high-level model APIs, protobuf for serialization, and grpcio for distributed computing—all pre-configured to work together.
This is a development release, updated frequently (typically daily), so it carries both the latest features and experimental code. It is intended for researchers, developers, and educators who want to test cutting-edge functionality on CPU hardware without waiting for stable releases. The CPU-only variant is lighter than GPU-enabled builds and suitable for environments where GPU acceleration is unavailable or unnecessary.
Use it for
- Prototyping numerical computation models on a development machine without GPU hardware.
- Testing new TensorFlow APIs and experimental features before they reach stable releases.
- Training small to medium models on CPU in resource-constrained environments.
- Running inference on edge devices or servers where GPU acceleration is not available.
- Educational projects and research where the latest TensorFlow features are needed.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need the latest TensorFlow development features and have a CPU-only environment or prefer not to manage GPU drivers.
No, if you require production stability—use a stable TensorFlow release instead. The nightly build is actively maintained and carries no known vulnerabilities, but development snapshots are inherently less tested than stable versions.
Install
tf-nightly-cpu on PyPI
Before you install
Medium install friction due to 20 runtime dependencies including numpy, keras-nightly, protobuf, and grpcio. Active maintenance with releases every few days; latest commit 2026-08-14. Requires Python >=3.10 and ships as compiled wheels for Python 3.11–3.14 on Linux and Windows.
Requires Python >=3.10; CPU-only build will not use GPU acceleration even if CUDA is present.
License in practice
Apache 2.0 permissive license allows commercial and private use with minimal restrictions, though you must include a copy of the license and note any modifications to the library itself.
Quickstart
pip install tf-nightly-cpu
import tf_nightly_cpuVerify before relying
- Whether nightly builds receive the same security review and stability guarantees as stable releases.
- Performance characteristics and numerical accuracy differences between nightly and stable versions.
- Compatibility matrix for specific hardware accelerators beyond the CUDA 12 classifiers listed.
Package facts
| License | Apache 2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 20 packagesabsl-pyastunparseflatbuffersgastgoogle_pastalibclangopt_einsumpackagingprotobufrequestssetuptoolssixtermcolortyping_extensionswraptgrpciokeras-nightlynumpyh5pyml_dtypes |
| Maintenance | Actively maintained 5 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 257,516 / month, #8,444 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: GPU :: NVIDIA CUDA :: 12Environment :: GPU :: NVIDIA CUDA :: 12 :: 12.0Intended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: MathematicsTopic :: Software DevelopmentTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python Modules |
Evidence: tf_nightly_cpu-2.22.0.dev20260809-cp311-cp311-manylinux_2_27_x86_64.whl; tf_nightly_cpu-2.22.0.dev20260809-cp312-cp312-manylinux_2_27_x86_64.whl; tf_nightly_cpu-2.22.0.dev20260809-cp313-cp313-manylinux_2_27_x86_64.whl; tf_nightly_cpu-2.22.0.dev20260809-cp313-cp313-win_amd64.whl; tf_nightly_cpu-2.22.0.dev20260809-cp314-cp314-manylinux_2_27_x86_64.whl
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See also tf-models-nightly · tf-nightly · tfx-bsl · tensorflow · tensorflow-cpu · tensorflow-cpu-aws · tensorflow-aarch64 · tensorflow-intel · tensorflow-hub · tfp-nightly