Lightning AI Studios vs ONNX Runtime
Lightning AI Studios
lightning.aiONNX Runtime
onnxruntime.aiSide by side
| Figure | Lightning AI Studios | ONNX Runtime |
|---|---|---|
| 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 | — |
| Self-hosted | Yes | Yes |
| Plans published | 9 | 1 |
| Spec score · Deep Learning Software | 9.1 (#1) | 8.4 (#6) |
| Integrations | The Studio documentation describes connecting S3 buckets and EFS volumes through Lightning Drive and importing models from Hugging Face and GitHub. | The ecosystem documentation lists integrations with Azure Machine Learning, Azure Custom Vision, Azure SQL Edge, Azure Synapse Analytics, ML.NET, and NVIDIA Triton Inference Server. |
| Purpose | AI Studio is a persistent, collaborative GPU cloud workspace for training models, running inference, building agents and AI apps, and coding together. | ONNX Runtime is a cross-platform machine-learning model accelerator with interfaces for hardware-specific libraries. |
| Support | Lightning lists email, Discord, and Twitter as support channels, and a dedicated Slack channel for enterprise support. | Documentation questions are directed to issue filing, and the project invites users to report bugs, suggest features, and submit pull requests on GitHub. |
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.
ONNX Runtime
ONNX Runtime is a free engine for machine-learning inference and training within existing technology stacks. It can run models from frameworks including PyTorch, TensorFlow/Keras, TFLite, and scikit-learn. For inference, it optimizes latency, throughput, memory use, and binary size through graph transformations, accelerator-aware partitioning, and optimized computation kernels. Its Execution Providers connect ONNX models to hardware acceleration libraries for CPUs, GPUs, FPGAs, and specialized NPUs. Listed options include NVIDIA CUDA and TensorRT, Intel OpenVINO, DirectML, Qualcomm QNN, Android NNAPI, Apple CoreML, and WebGPU. Deployment spans cloud servers, edge and mobile devices, and browsers; its web runtime supports browser models and its mobile runtime supports Android and iOS. Supported languages include Python, C#, C++, Java, JavaScript, and Rust. Developers can create smaller web or mobile packages by including only the operators and opsets their models need. The open-source runtime is available on Android, iOS, Linux, macOS, self-hosted environments, web, and Windows.