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Lightning AI Studios vs MegEngine

Lightning AI Studios

lightning.ai

MegEngine

megengine.org.cn

Side by side

FigureLightning AI StudiosMegEngine
Price from$20/moFree
Free planYesYes
Free trialYes—
Open source——
WebYes—
WindowsYesYes
macOSYesYes
LinuxYesYes
iOS—Yes
Android—Yes
APIYes—
Self-hostedYesYes
Plans published91
Spec score · Deep Learning Software9.1 (#1)7.9 (#15)
IntegrationsThe Studio documentation describes connecting S3 buckets and EFS volumes through Lightning Drive and importing models from Hugging Face and GitHub.MegFile provides Python file interfaces for S3, HTTP and local files.
Intended usersThe pricing page describes Free for students, researchers, and hobbyists; Pro for developers, researchers, and scientists; and Teams for research labs and small teams.The official site presents tutorials for beginners and advanced developers and describes the framework as supporting model development through deployment.
PurposeAI Studio is a persistent, collaborative GPU cloud workspace for training models, running inference, building agents and AI apps, and coding together.MegEngine is a fast, scalable deep learning framework with automatic differentiation.
SupportLightning lists email, Discord, and Twitter as support channels, and a dedicated Slack channel for enterprise support.The project lists GitHub issues, a forum, QQ group and [email protected] for contact.

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

Lightning AI Studios pricing →

MegEngine

  • MegEngineFree

MegEngine pricing →

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.

Visit lightning.ai

MegEngine

MegEngine is a free, open-source deep learning framework for developing and deploying models, with automatic differentiation. It uses one model for training and inference, including quantization and dynamic shapes. The project says enabling DTR can reduce GPU memory use to one-third of the original. Inference is supported across x86, Arm, CUDA, and ROCm; GPU use requires compatible device drivers. Python packages are listed for 64-bit Linux and Windows, macOS 10.14 or later, and Android 7 or later, though macOS and Android installations are CPU-only. The installation guide specifies Python 3.6–3.9. MegEngine Lite supplies C/C++, Rust, and Python runtimes for deployment. MgeConvert handles conversion between MegEngine and third-party model formats, MegFile provides Python file interfaces for S3, HTTP, and local files, and MegFlow is a streaming computation framework for AI applications. Tutorials address beginners and advanced developers. Support options include GitHub issues, a forum, a QQ group, and email.

Visit megengine.org.cn