Developer Frameworks & Infrastructure
TensorFlow
Google's end-to-end machine learning platform
Open sourceRuns on your device
Pricing
Open Source
Free
Platforms
macOS - Windows - Linux
Self-hosted or local
Category
Developer Frameworks & Infrastructure
133 tools
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Last updated
Sep 23
Listing updated
Best for
Ship models to mobile and edge
Convert trained models with the LiteRT runtime to run offline on phones, embedded devices, and microcontrollers.
Pricing checked Sep 2026
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About TensorFlow
TensorFlow is Google's open-source machine learning platform, covering the full path from experimentation to deployment. Keras provides the high-level API that most people actually write, while TFX pipelines, TensorBoard profiling, and serving infrastructure support production systems at scale. The framework spans servers, browsers through TensorFlow.js, and edge devices through the mobile runtime, now branded LiteRT.
PyTorch has taken over research mindshare, but TensorFlow retains strengths where deployment breadth matters: mature mobile and embedded support, JavaScript inference without a server, and enterprise tooling for pipelines and monitoring. Hardware support runs from CPUs to Google's TPUs. Governed under Apache 2.0 with heavy Google involvement, it suits teams shipping models to apps, browsers, and microcontrollers, and organizations standardizing on Google Cloud tooling; pure research teams generally default to PyTorch.
- End-to-end coverage from research code to served production models
- Best-in-class mobile, embedded, and browser deployment runtimes
- Keras API keeps common tasks approachable
- Apache 2.0 license with strong documentation and long-term support
- Research community has largely moved to PyTorch
- Legacy TF 1.x APIs and Keras transitions still confuse newcomers
- Debugging inside graph execution is less direct than eager PyTorch
pip install tensorflowEnd-to-end machine learning platform for training and deploying deep learning models.
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