Lightning AI Studios vs TensorFlow
Lightning AI Studios
lightning.aiTensorFlow
tensorflow.orgSide by side
| Figure | Lightning AI Studios | TensorFlow |
|---|---|---|
| Price from | $20/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 9 | 1 |
| Spec score · Deep Learning Software | 9.1 (#1) | 7.5 (#22) |
| Integrations | The Studio documentation describes connecting S3 buckets and EFS volumes through Lightning Drive and importing models from Hugging Face and GitHub. | The TFX pipeline tutorial describes exporting pipeline source code that can be orchestrated with Apache Airflow and Apache Beam. |
| Support | Lightning lists email, Discord, and Twitter as support channels, and a dedicated Slack channel for enterprise support. | TensorFlow directs users to its issue tracker, release notes, Stack Overflow, community forum, and announcement mailing list. |
Plans
Lightning AI Studios
- FreeFree
- FreeFree
- Pro$20 a month
- Pro (annual)$20 a month
- Pro (monthly)$50 a month
- Teams$119 a month
- Teams (annual)$119 a month
- Teams (monthly)$140 a month
- EnterprisePriced on request
In their own words
Lightning AI Studios
Lightning AI Studios is a cloud workspace for training models, running inference, building agents and AI apps, and coding collaboratively. Its persistent environments save installed packages, custom Python versions, and downloaded files. Studios offer browser-accessible VS Code and JupyterLab, plus AI copilots for AI and machine-learning work, including CUDA and PyTorch debugging. Teams can collaborate in real time on private projects, use a full-stack runtime, and deploy full-stack applications. Users can connect S3 buckets and EFS volumes through Lightning Drive, import models from Hugging Face and GitHub, or connect local IDEs such as VS Code, Cursor, and PyCharm over SSH. An SDK supports workflow automation. The Free plan is free and includes one active Studio, 50 GB persistent storage, and up to two concurrent GPUs; that Studio requires a restart every four hours. Pro and Teams plans have higher storage and GPU limits. Enterprise offers deployment in a customer VPC using AWS or GCP cloud credits.
TensorFlow
TensorFlow is a free, open-source platform for creating machine learning models and running them in different environments. Model-building options include the high-level Keras API, eager execution, and distributed training tools. Models can be deployed on servers, edge devices, and the web: TFX supports production pipelines, TensorFlow Lite supports mobile and edge inference, and TensorFlow.js covers JavaScript environments. The ecosystem also includes LiteRT, tf.data, TensorFlow Datasets, and TensorBoard. TensorFlow provides resources addressing fairness, interpretability, privacy, and security in machine learning workflows, including TF Privacy for privacy-focused training and TF Federated for federated learning. Supported 64-bit environments include Ubuntu, Windows, and macOS; WSL2 GPU support is marked experimental. TensorFlow's install guide states that macOS has no GPU support. Google Colab can run TensorFlow tutorials in browser-based Jupyter notebooks without installation or setup. The API and reference implementation were released under the Apache 2.0 license in November 2015. Listed platforms include Android, iOS, Linux, macOS, self-hosted, web, and Windows.