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lightning GPU Cloud Provider
Lightning AI is a cloud platform built for AI developers, researchers, and teams, offering scalable GPU and CPU compute resources to accelerate model training, development, and deployment. With flexible pricing tiers, it supports everything from individual hobbyists to enterprise-grade needs, providing Studios with persistent storage, multi-GPU capabilities, and seamless integration with local IDEs and cloud services.
Provider Overview
| Name | lightning |
| Total Instances | 4 |
| Minimum Price | $0.68/hr |
| Maximum VRAM | 48 GB |
| Available GPU Models | A10G, L4, L40S, T4 |
Lightning AI is a cloud platform built for AI developers, researchers, and teams, offering scalable GPU and CPU compute resources to accelerate model training, development, and deployment. With flexible pricing tiers, it supports everything from individual hobbyists to enterprise-grade needs, providing Studios with persistent storage, multi-GPU capabilities, and seamless integration with local IDEs and cloud services.
About the Provider
Pricing Plans
Free
$0
For students, researchers, and hobbyists.
✓ Save ~80% with interruptible (spot)
✓ Unlimited background execution
✓ 32 core CPU Studios
✓ Connect any local IDE or ssh
✓ Persistent storage (100GB limit)
Pro
$50
For developers, researchers, and scientists.
✓ Multi-GPU Studios
✓ 64 and 96 core CPU Studios
✓ Multi-node training (up to 4 machines)
✓ Persistent storage (2TB limit)
✓ Connect public, private S3 buckets
Teams
$140
For teams and startups.
✓ Use Lightning GPU quotas or your own
✓ Multi-node training (up to 32 machines)
✓ Use via AWS marketplace
✓ Persistent storage (unlimited)
✓ Real-time cost controls
Available Instances
| Accelerator | Provider | Price | VRAM | Type |
|---|---|---|---|---|
| T4 |
lightning |
$0.68/hr | 16 GB | Turing |
| L4 |
lightning |
$0.70/hr | 24 GB | Ada Lovelace |
| A10G |
lightning |
$1.80/hr | 24 GB | Ampere |
| L40S |
lightning |
$2.17/hr | 48 GB | Ada Lovelace |
Ready to Get Started?
Visit lightning's website to create an account and start using their GPU instances.