A cloud platform from the creators of PyTorch Lightning for building, training, and deploying ML models, with on-demand GPUs, clusters, and AI coding agents.
About
Lightning AI is a cloud development platform for building, training, and deploying custom machine learning models. It addresses a common problem for AI teams: instead of relying on rented, general-purpose AI services or managing their own GPU infrastructure, teams get guaranteed on-demand GPUs, multi-node clusters, AI coding agents, and enterprise-grade infrastructure in a single environment.
The platform is built by the creators of PyTorch Lightning, a widely used open-source deep learning framework, and the site states it is trusted by more than 450,000 developers and AI teams. Lightning AI covers the full model lifecycle in cloud-based Studios: preparing datasets, prototyping and optimizing models, running and comparing experiments, pretraining and post-training (including reinforcement learning in sandboxes), evaluating accuracy and safety, and serving inference at scale. Compute is billed by the second, and the platform supports enterprise options such as running on a private cloud or VPC.
Key Features
Pricing & Fees
- Pricing: Free tier with up to 80 free GPU hours and one Studio running 24/7 (free Studios restart every 4 hours); pay-as-you-go after that, with per-GPU rates such as $0.55/hr for a T4, $1.85/hr for an A100 (80 GB), $5.45/hr for an H100 (80 GB), $4.50/hr for an H200 (141 GB), and $9.86/hr for a B200. Enterprise plans are quoted on request.
- Interruptible rates: Lower per-second rates are available for interruptible compute on many instance types.
- Free tier: No credit card required, with up to 30 free credits to start; academic pricing is also offered.
- TPUs and clusters: TPU instances (1, 4, and 8 TPU configurations) and multi-machine clusters with A100, H100, H200, or B200 GPUs are available by inquiry.
Who It's For
Lightning AI is aimed at machine learning engineers, AI researchers, and data scientists who need to develop and train their own specialized models rather than call general-purpose APIs. It suits academic labs and individual researchers (academic pricing is available), startup AI teams, and enterprise ML organizations that need budget controls, compliance, and private-cloud deployment. Published customer stories include cancer research teams, edge-AI model developers, and consulting firms building client ML pipelines, illustrating use cases from research iteration to production inference.
FAQ
What is Lightning AI?Lightning AI is a cloud platform, built by the creators of PyTorch Lightning, that lets developers build, train, and deploy their own machine learning models using on-demand GPUs, clusters, AI coding agents, and enterprise infrastructure.
Is there a free plan for Lightning AI?Yes, the free tier includes up to 80 free GPU hours and one Studio that runs 24/7 (with a restart required every 4 hours), with no credit card needed; additional usage is pay-as-you-go and billed by the second.
How much do GPUs cost on Lightning AI?Listed pay-as-you-go rates include $0.55 per GPU-hour for a T4, $1.85 for an A100 (80 GB), $4.50 for an H200 (141 GB), $5.45 for an H100 (80 GB), and $9.86 for a B200, with discounts available for interruptible instances on some types.
Which clouds and integrations does Lightning AI support?The platform can access AWS, GCP, Lightning, Lambda, Nebius, and NScale capacity, and enterprise customers can run Lightning on their own private cloud or VPC, including on Kubernetes or Slurm stacks.
Is Lightning AI suitable for regulated workloads?The company states SOC 2 and HIPAA compliance, GDPR support, encryption at rest and in transit, audit logs, SSO with role-based access, and fine-grained data access controls, which are relevant for regulated environments.
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