> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/deployment/self-hosted/inference-server/configuration/docker-configuration.md).

# Docker Configuration Options

Configure a self-hosted Roboflow Inference container - networking, CORS, NMS defaults, model cache, workers, HTTPS, and the Secure Gateway.

Inference servers have a number of configurable parameters that you set with environment variables. To set an environment variable with `docker run`, use the `-e` flag:

```bash
docker run -it --rm -e ENV_VAR_NAME=env_var_value -p 127.0.0.1:9001:9001 --gpus all roboflow/roboflow-inference-server-gpu:latest
```

This page covers the options you are most likely to change. For the complete list, see [Environment Variables](/deployment/self-hosted/inference-server/configuration/environment-variables.md).

## Networking

`HOST`: string (default `0.0.0.0`). Selects the interface inside the container; keep this value for Docker bridge networking so published ports can reach the server.

Use the host-side mapping `-p 127.0.0.1:9001:9001` for local-only access, or deliberately select a LAN interface. The CLI's `--bind-address` controls that mapping; macOS and Windows desktop bundles instead use `HOST`, defaulting to `127.0.0.1`. See [network access](/deployment/self-hosted/inference-server/configuration/security.md#restrict-network-access) for Jetson and tunnel exceptions.

**`PORT`**: integer (default `9001`). Sets the port used by HTTP interfaces.

**`ALLOW_ORIGINS`**: string (default `*`). Sets the `allow_origins` property on the CORS middleware used with FastAPI for HTTP interfaces. Multiple values can be provided separated by a comma, for example `ALLOW_ORIGINS=orig1.com,orig2.com`.

## Inference behavior

**`CLASS_AGNOSTIC_NMS`**: boolean (default `False`). Sets the default non-maximum suppression (NMS) behavior for detection models (object detection, instance segmentation, and similar). When `True`, NMS is class agnostic, so overlapping detections from different classes may be removed based on the IoU threshold. When `False`, only overlapping detections from the same class are considered for removal.

**`MAX_CANDIDATES`**: integer (default `3000`). The maximum number of candidates for detection.

**`MAX_DETECTIONS`**: integer (default `300`). The maximum number of detections returned by a model.

**`FIX_BATCH_SIZE`**: boolean (default `False`). When `True`, the batch size is fixed to the maximum batch size configured for this server.

**`MAX_ACTIVE_MODELS`**: integer (default `8`). The maximum number of models the internal model manager keeps in memory at one time. By default the model queue removes the least recently accessed model when making space for a new one.

**`NUM_WORKERS`**: integer (default `1`). The number of workers used by HTTP interfaces.

## CLIP model options

**`CLIP_VERSION_ID`**: string (default `ViT-B-16`). Sets the OpenAI CLIP version used by all `/clip` routes. Available versions are `RN101`, `RN50`, `RN50x16`, `RN50x4`, `RN50x64`, `ViT-B-16`, `ViT-B-32`, `ViT-L-14-336px`, and `ViT-L-14`.

**`CLIP_MAX_BATCH_SIZE`**: integer (default `8`). Sets the max batch size accepted by the CLIP model inference functions.

## Model cache

**`MODEL_CACHE_DIR`**: string (default `/tmp/cache`). Sets the container path for the root model cache directory.

**`TENSORRT_CACHE_PATH`**: string (default: the value of `MODEL_CACHE_DIR`). Sets the container path to the TensorRT cache directory. Setting this path together with a mounted host volume reduces the cold start time of TensorRT-based servers.

### Persistent model cache

By default model weights are stored inside the container at `/tmp/cache` and are **lost on container restart or system reboot**. For production deployments, mount a persistent host volume to preserve downloaded weights:

```bash
# Create a persistent cache directory on the host
mkdir -p /var/lib/roboflow/cache

# Run the container with a persistent cache
docker run -d \
  -p 127.0.0.1:9001:9001 \
  -v /var/lib/roboflow/cache:/tmp/cache \
  -e MODEL_CACHE_DIR=/tmp/cache \
  roboflow/roboflow-inference-server-cpu:latest
```

Things to keep in mind:

* The host path should be on persistent storage, not in `/tmp`.
* The mounted directory needs appropriate permissions for the container user (typically UID 1000 or root, depending on the image).
* A persistent cache lets you pre-populate weights before deployment and keeps them across container updates.

See [Offline weights download](https://docs.roboflow.com/reference/inference/inference-python/offline-weights) for more on pre-downloading and caching weights.

## HTTPS / TLS

**`ENABLE_HTTPS`**: boolean (default `False`). When set, the Inference Server serves traffic over HTTPS instead of HTTP, reading the certificate and private key from `SSL_CERTFILE` and `SSL_KEYFILE`.

**`SSL_CERTFILE`**: string (default `/etc/inference/certs/server.crt`) and **`SSL_KEYFILE`**: string (default `/etc/inference/certs/server.key`). Paths to the PEM-encoded certificate and private key inside the container. The defaults are convenient mount points, so usually you only need to bind your cert and key into `/etc/inference/certs/` and set `ENABLE_HTTPS=true`.

`SSL_KEYFILE_PASSWORD`: string (optional). Supplies an encrypted private key's passphrase to Uvicorn launchers; the parallel Gunicorn launcher does not support it.

`SSL_CA_CERTS`: string (optional). Supplies the client CA bundle for mTLS when HTTPS is enabled. See [HTTPS configuration](/deployment/self-hosted/inference-server/configuration/https.md#mutual-tls) for enforcement and release scope.

Full walkthrough with self-signed certificates: [Serving Inference over HTTPS](/deployment/self-hosted/inference-server/configuration/https.md).

## Secure Gateway

**`SECURE_GATEWAY`**: string (default unset). Sets the address of a [Roboflow Secure Gateway](/deployment/self-hosted/enterprise/secure-gateway.md) for air-gapped deployments. Roboflow API and model download traffic is routed through this proxy. Traffic that cannot be proxied is disabled or rerouted as follows:

* The Inference version check (which calls `api.github.com`) is force-disabled: `DISABLE_VERSION_CHECK` is set to `True` even if explicitly configured otherwise.
* If `WORKFLOWS_STEP_EXECUTION_MODE=remote` is combined with `WORKFLOWS_REMOTE_API_TARGET=hosted`, step execution falls back to `local` with a warning, because the hosted Roboflow inference endpoints cannot be reached through the gateway proxy. To keep remote execution, use `WORKFLOWS_REMOTE_API_TARGET=self-hosted` **and** point `LOCAL_INFERENCE_API_URL` (default `http://127.0.0.1:9001`) at an Inference server reachable inside the gateway perimeter.
* Third-party integrations (Google Vision and Gemini direct-key paths, Stability AI, Twilio media upload, webhooks to external hosts) are not proxied and will fail unless the gateway network permits them.

Use an explicit HTTPS gateway URL, such as `SECURE_GATEWAY=https://gateway.example.com`, and trust the gateway certificate. The pending runtime-hardening build changes bare addresses to HTTPS and rejects non-loopback plaintext gateways; see [migration scope](/deployment/self-hosted/inference-server/configuration/security-migration.md#gateway-transport).

The legacy `LICENSE_SERVER` environment variable is still accepted but deprecated.