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Lambda Labs: GPU Unavailable / No Capacity
Current Status: Major Outage
Last checked: 7m ago
What We're Seeing Right Now
No recent issues reported. If you're experiencing problems with Lambda Labs, report below to help the community.
What is this error?
When Lambda Labs reports no GPU availability, there are no compute resources to run your model. GPU scarcity is a major issue in AI infrastructure, especially for high-demand GPU types like A100 and H100.
Error Signatures
No GPU availableGPU capacity exceededNo available machinesResource not availableInsufficient capacityOut of capacityNo instances availableGPU quota exceededCommon Causes
- All GPUs of the requested type are in use
- Regional capacity exhausted
- Spot/preemptible instances were reclaimed
- Specific GPU type not available in your region
- Lambda Labs is experiencing a capacity crunch
✓ How to Fix It
- Try a different GPU type (e.g., A10 instead of A100)
- Try a different region
- Use on-demand instead of spot instances
- Set up auto-retry with Lambda Labs's queue system
- Check this page for capacity updates
- Consider reserved instances for guaranteed access
Live Signals
Service Components
Lambda Cloud
OperationalRecent Incidents
No incidents in the past 30 days
Frequently Asked Questions
Why are Lambda Labs GPUs unavailable?
GPU demand exceeds supply, especially for popular types. Try different GPU types, regions, or off-peak hours.
When will Lambda Labs GPUs be available?
Capacity fluctuates. Check community reports for real-time availability feedback.
How do I get guaranteed GPU access on Lambda Labs?
Consider reserved instances, enterprise plans, or multi-provider setups.