Lambda Labs Status — Is Lambda Labs Down?

Operational

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Service Status

Lambda Cloud

Operational638ms

24-Hour Uptime

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Operational

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Recent Incidents

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Common Issues with Lambda Labs

See detailed troubleshooting guides for the most common Lambda Labs errors:

GPU Unavailable / No Capacity

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.

Deployment Failed / Build Error

When Lambda Labs fails to deploy your model or application, the build, packaging, or startup process encountered an error. This can block your production pipeline.

Inference Timeout / Model Loading Error

When Lambda Labs inference times out, the model took too long to load, initialize, or generate a response. Large models can have cold start times of 30-120 seconds, and inference itself can timeout under load.

Region Unavailable / Endpoint Down

When a Lambda Labs region or endpoint is unavailable, the specific data center or geographic zone you're targeting is down or unreachable. Other regions may still be operational.

Account / Billing Suspended

When Lambda Labs suspends your account due to billing issues, all your deployments, API access, and resources are paused or terminated. This can happen silently and cause production outages.

About Lambda Labs

GPU cloud for AI training and inference

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Lambda Cloud