> For clean Markdown content of this page, append .md to this URL. For the complete documentation index, see https://docs.nvidia.com/dynamo/llms.txt. For full content including API reference and SDK examples, see https://docs.nvidia.com/dynamo/llms-full.txt.

# Model Storage Overview

Dynamo deployments often need shared storage before the first model pod starts. Use this page to choose the right storage path for model weights, backend compilation artifacts, and cache data, then follow the provider-specific setup guide for your cluster.

## What Needs Storage

| Data | Why it matters | Typical requirement |
|---|---|---|
| Model weights and tokenizer files | Avoid repeated downloads and give all workers the same model artifacts. | Persistent storage with enough throughput for cold starts and scale-out. |
| Backend compilation artifacts | Reuse compiled engines or kernels when the same model and GPU shape starts again. | Persistent or fast node-local storage, depending on backend and deployment pattern. |
| Runtime cache and scratch data | Keep temporary data close to workers during serving. | Fast ephemeral or node-local storage. |

Storage is especially important for large models and multi-node deployments. A slow or single-node model store can dominate cold-start time even when the serving stack is configured correctly.

## Choose a Storage Option

| Environment | Start here | Best fit |
|---|---|---|
| AKS | [Storage for Model Caching on AKS](/dynamo/dev/kubernetes/installation/model-storage/aks-storage) | Compare Azure Disk, Azure Files, Azure Blob, local CSI, and Azure Managed Lustre. |
| AKS with high-throughput shared storage | [Azure Lustre CSI Driver](/dynamo/dev/kubernetes/installation/model-storage/azure-lustre-csi-driver) | Configure Azure Managed Lustre for large shared model caches. |
| EKS | [Amazon EFS Setup for EKS](/dynamo/dev/kubernetes/installation/model-storage/efs) | Share model weights and compilation cache across EKS nodes. |
| Any Kubernetes cluster | [Model Caching](/dynamo/dev/kubernetes/model-deployment/model-loading/model-caching) | Wire a cache PVC into Dynamo model loading and deployment templates. |

## Selection Guidelines

- Use high-throughput shared storage for large models that start on multiple nodes or replicas.
- Use persistent storage for model weights when repeated downloads would slow cold starts or stress object storage.
- Use fast ephemeral or node-local storage for scratch data that does not need to survive pod replacement.
- Confirm the storage class supports the access mode your deployment needs, such as `ReadWriteMany` for shared model caches.
- Validate throughput during a scale-out test, not only with a single pod.

## Next Steps

1. Pick the storage guide that matches your cloud provider.
2. Create or verify the storage class and persistent volume claims.
3. Follow [Model Caching](/dynamo/dev/kubernetes/model-deployment/model-loading/model-caching) to connect the storage to a Dynamo deployment.