> 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/deploy.md).

# Deploy

- [Deploy a Model or Workflow](https://docs.roboflow.com/deploy/deployment-overview.md): Learn how to deploy workflows and models trained on or uploaded to Roboflow.
- [Supported Models](https://docs.roboflow.com/deploy/supported-models.md): All models you can deploy with Roboflow.
- [RF-DETR](https://docs.roboflow.com/deploy/supported-models/rf-detr.md): Use Roboflow's RF-DETR model through our Serverless Hosted API
- [Roboflow 3.0](https://docs.roboflow.com/deploy/supported-models/roboflow-3.md): Use the Roboflow 3.0 model family through our Serverless Hosted API
- [YOLOLite](https://docs.roboflow.com/deploy/supported-models/yololite.md): Use the YOLOlite model family through our Serverless Hosted API
- [Cosmos 3 Edge](https://docs.roboflow.com/deploy/supported-models/cosmos-3-edge.md): Use NVIDIA's Cosmos 3 Edge vision-language world model through our Serverless Hosted API
- [Qwen3.5](https://docs.roboflow.com/deploy/supported-models/qwen3-5.md): Use Alibaba's Qwen3.5-VL vision-language model through Workflows, Dedicated Deployments, or self-hosted Inference
- [GLM-OCR](https://docs.roboflow.com/deploy/supported-models/glm-ocr.md): Use GLM-OCR for image OCR through our Serverless Hosted API
- [SAM3](https://docs.roboflow.com/deploy/supported-models/sam3.md): Use Meta's SAM3 model through our Serverless Hosted API
- [YOLO26](https://docs.roboflow.com/deploy/supported-models/yolo26.md): Use the YOLO26 model family through our Serverless Hosted API
- [Qwen3-VL](https://docs.roboflow.com/deploy/supported-models/qwen3-vl.md): Use Alibaba's Qwen3-VL vision-language model through our Serverless Hosted API
- [Dino v3](https://docs.roboflow.com/deploy/supported-models/dino-v3.md): Run DINOv3 classification models trained on Roboflow via the Serverless Hosted API
- [Roboflow Instant](https://docs.roboflow.com/deploy/supported-models/roboflow-instant.md): Run a Roboflow Instant few-shot object detection model via the Serverless Hosted API.
- [Perception Encoder](https://docs.roboflow.com/deploy/supported-models/perception-encoder.md): Use Meta's Perception Encoder to compute image and text embeddings on a Dedicated Deployment or self-hosted Inference
- [SmolVLM2](https://docs.roboflow.com/deploy/supported-models/smolvlm2.md): Use HuggingFace's SmolVLM2 vision-language model on a Dedicated Deployment or self-hosted Inference
- [YOLOv12](https://docs.roboflow.com/deploy/supported-models/yolov12.md): Use the YOLOv12 object detection model through our Serverless Hosted API
- [PaliGemma 2](https://docs.roboflow.com/deploy/supported-models/paligemma2.md): Use Google's PaliGemma 2 vision-language model through our Serverless Hosted API
- [YOLO11](https://docs.roboflow.com/deploy/supported-models/yolo11.md): Use the YOLO11 model family through our Serverless Hosted API
- [SAM2](https://docs.roboflow.com/deploy/supported-models/sam2.md): Use Meta's SAM2 model through our Serverless Hosted API
- [Florence 2](https://docs.roboflow.com/deploy/supported-models/florence-2.md): Use Microsoft's Florence 2 multimodal model through our Serverless Hosted API
- [Depth Anything V2](https://docs.roboflow.com/deploy/supported-models/depth-anything-v2.md): Use Depth Anything V2 for monocular depth estimation on a Dedicated Deployment or self-hosted Inference
- [Moondream2](https://docs.roboflow.com/deploy/supported-models/moondream2.md): Use Moondream2 for open-vocabulary detection on a Dedicated Deployment or self-hosted Inference
- [YOLOv9](https://docs.roboflow.com/deploy/supported-models/yolov9.md): Use YOLOv9 object detection through our Serverless Hosted API
- [YOLO-World](https://docs.roboflow.com/deploy/supported-models/yolo-world.md): Use YOLO-World open-vocabulary object detection through our Serverless Hosted API
- [OwlV2](https://docs.roboflow.com/deploy/supported-models/owlv2.md): Use OwlV2 for one-shot object detection on a Dedicated Deployment or self-hosted Inference
- [Grounding DINO](https://docs.roboflow.com/deploy/supported-models/grounding-dino.md): Use Grounding DINO for text-prompted object detection on a Dedicated Deployment or self-hosted Inference
- [YOLOv7](https://docs.roboflow.com/deploy/supported-models/yolov7.md): Use YOLOv7 instance segmentation through our Serverless Hosted API
- [Roboflow 2.0](https://docs.roboflow.com/deploy/supported-models/roboflow-2.md): Use the Roboflow 2.0 semantic segmentation model through our Serverless Hosted API
- [L2Cs-Net](https://docs.roboflow.com/deploy/supported-models/l2cs-net.md): Use L2Cs-Net gaze detection model through our Serverless Hosted API
- [TrOCR](https://docs.roboflow.com/deploy/supported-models/trocr.md): Use Microsoft's TrOCR for text recognition on a Dedicated Deployment or self-hosted Inference
- [DocTR](https://docs.roboflow.com/deploy/supported-models/doctr.md): Use the DocTR OCR model through our Serverless Hosted API
- [CLIP](https://docs.roboflow.com/deploy/supported-models/clip.md): Use OpenAI's CLIP model through our Serverless Hosted API
- [ViT](https://docs.roboflow.com/deploy/supported-models/vit.md): Run ViT classification models trained on Roboflow via the Serverless Hosted API
- [EasyOCR](https://docs.roboflow.com/deploy/supported-models/easyocr.md): Use the EasyOCR multilingual OCR model through our Serverless Hosted API
- [ResNet](https://docs.roboflow.com/deploy/supported-models/resnet.md): Use ResNet image classification through our Serverless Hosted API
- [Serverless Hosted API](https://docs.roboflow.com/deploy/serverless-hosted-api-v2.md): Run Workflows and Model Inference on GPU-accelerated auto-scaling infrastructure in the Roboflow cloud.
- [Use in a Workflow](https://docs.roboflow.com/deploy/serverless-hosted-api-v2/use-in-a-workflow.md): You can use Serverless Hosted API with Roboflow Workflows.
- [Use with the REST API](https://docs.roboflow.com/deploy/serverless-hosted-api-v2/use-with-the-rest-api.md)
- [Use with Python SDK](https://docs.roboflow.com/deploy/serverless-hosted-api-v2/use-with-python-sdk.md): Use Roboflow's Serverless Hosted API with Python SDK
- [Pricing](https://docs.roboflow.com/deploy/serverless-hosted-api-v2/pricing.md): Serverless Hosted API Pricing page
- [Serverless Video Streaming API](https://docs.roboflow.com/deploy/serverless-video-streaming-api.md): Run Roboflow Workflows on live video in the Roboflow Cloud. Stream input from webcams, RTSP cameras, or video files via WebRTC and receive inference results back in your application.
- [Batch Processing](https://docs.roboflow.com/deploy/batch-processing.md)
- [Run Workflows from the App](https://docs.roboflow.com/deploy/batch-processing/run-from-the-app.md): Start Batch Processing jobs from the Roboflow app, on demand or automatically each time a Datasource mirrors a cloud bucket.
- [API Reference](https://docs.roboflow.com/deploy/batch-processing/api-reference.md): REST API reference for Batch Processing endpoints.
- [CLI Usage](https://docs.roboflow.com/deploy/batch-processing/cli-usage.md): Use the Roboflow CLI to create and manage Batch Processing jobs.
- [Troubleshooting](https://docs.roboflow.com/deploy/batch-processing/troubleshooting.md): Troubleshoot common Batch Processing issues including timeouts, SAHI performance, and OOM errors.
- [Dedicated Deployments](https://docs.roboflow.com/deploy/dedicated-deployments.md): Run Your Vision Models on Dedicated Servers with Roboflow
- [Create a Dedicated Deployment](https://docs.roboflow.com/deploy/dedicated-deployments/create-a-dedicated-deployment.md): You can create a Dedicated Deployment in the Roboflow web interface, or in the CLI.
- [Pause and Resume a Dedicated Deployment](https://docs.roboflow.com/deploy/dedicated-deployments/pause-and-resume-a-dedicated-deployment.md)
- [Delete a Dedicated Deployment](https://docs.roboflow.com/deploy/dedicated-deployments/delete-a-dedicated-deployment.md)
- [Make Requests to a Dedicated Deployment](https://docs.roboflow.com/deploy/dedicated-deployments/make-requests-to-a-dedicated-deployment.md): You can make requests to a Dedicated Deployment directly with the Python SDK, using a HTTP API, or using the Workflows web interface.
- [Manage Dedicated Deployments with an API](https://docs.roboflow.com/deploy/dedicated-deployments/manage-dedicated-deployments-with-an-api.md): Manage your dedicated deployment using our HTTP APIs.
- [Managed Deployments](https://docs.roboflow.com/deploy/roboflow-managed-deployments-overview.md)
- [Self-Hosted Deployment](https://docs.roboflow.com/deploy/self-hosted-deployment.md): You can run Roboflow models and Workflows on your own hardware.
- [Other SDKs](https://docs.roboflow.com/deploy/sdks.md)
- [Python inference-sdk](https://docs.roboflow.com/deploy/sdks/python-inference-sdk.md): Information about inference-sk
- [Web Browser](https://docs.roboflow.com/deploy/sdks/web-browser.md)
- [Web inference.js](https://docs.roboflow.com/deploy/sdks/web-browser/web-inference.js.md): Run realtime predictions at the edge, on the browser, with inference.js
- [inferencejs Reference](https://docs.roboflow.com/deploy/sdks/web-browser/web-inference.js/inferencejs-reference.md): Reference for \`inferencejs\`, an edge library for deploying computer vision applications built with Roboflow to web/JavaScript environments
- [inferencejs Requirements](https://docs.roboflow.com/deploy/sdks/web-browser/web-inference.js/inferencejs-requirements.md): Requirements for running \`inferencejs\`
- [Web inference-sdk](https://docs.roboflow.com/deploy/sdks/web-browser/web-inference-sdk.md): Run realtime video inference from your browser, running on the Roboflow cloud, with inference-sdk
- [Lens Studio](https://docs.roboflow.com/deploy/sdks/lens-studio.md): Deploy a model to Lens Studio for use in building a Snap Lens.
- [Changelog - Lens Studio](https://docs.roboflow.com/deploy/sdks/lens-studio/changelog-lens-studio.md): A list of public facing changes for the Lens Studio integration
- [Luxonis OAK](https://docs.roboflow.com/deploy/sdks/luxonis-oak.md): Deploy your Roboflow Train model to your OpenCV AI Kit with Myriad X VPU  acceleration.
- [OpenMV](https://docs.roboflow.com/deploy/sdks/openmv.md): Deploy computer vision models to extremely low power edge cameras.
- [iOS SDK](https://docs.roboflow.com/deploy/sdks/ios-sdk.md): Deploy your trained Roboflow model in your iOS app
- [Upload Custom Model Weights](https://docs.roboflow.com/deploy/upload-custom-weights.md): Roboflow offers the ability to upload model weights for your custom-trained models to your Roboflow projects for model deployment.
- [Download Model Weights](https://docs.roboflow.com/deploy/download-roboflow-model-weights.md): To run your Roboflow models on your own hardware, you can either use Roboflow Inference (the recommended, automatic method) or manually download Model Weights (for specific edge cases).
- [Enterprise Deployment](https://docs.roboflow.com/deploy/enterprise-deployment.md)
- [Secure Gateway](https://docs.roboflow.com/deploy/enterprise-deployment/secure-gateway.md): Secure Gateway proxies the routes Roboflow Deployment servers need into your company's DMZ, and caches model weights and container images locally.
- [License Server (Deprecated)](https://docs.roboflow.com/deploy/enterprise-deployment/license-server.md): You can use the Roboflow License server to proxy the necessary routes for Roboflow Deployment servers into your company's DMZ
- [Offline Mode](https://docs.roboflow.com/deploy/enterprise-deployment/offline-mode.md): Roboflow Enterprise customers can deploy models offline.
- [Kubernetes](https://docs.roboflow.com/deploy/enterprise-deployment/kubernetes.md): Getting started with Roboflow Inference on Kubernetes
- [Docker Compose](https://docs.roboflow.com/deploy/enterprise-deployment/docker-compose.md): Run the Roboflow inference server alongside other docker containers to build your multi-container application via Docker Compose.
- [Deployment Manager](https://docs.roboflow.com/deploy/device-manager.md): Manage and monitor computer vision models deployed on edge hardware.
- [Setting Up](https://docs.roboflow.com/deploy/device-manager/setting-up.md)
- [Hardware Requirements](https://docs.roboflow.com/deploy/device-manager/setting-up/hardware-requirements.md)
- [Add a Device](https://docs.roboflow.com/deploy/device-manager/setting-up/add-a-device.md): Set up a device with everything you need to deploy a Workflow using Deployment Manager.
- [Add a Stream](https://docs.roboflow.com/deploy/device-manager/setting-up/add-a-stream.md): Learn how to configure a stream that you can use to run a Workflow.
- [Setup Maintenance Windows](https://docs.roboflow.com/deploy/device-manager/setting-up/setup-maintenance-windows.md)
- [Set up Device Alerts](https://docs.roboflow.com/deploy/device-manager/setting-up/set-up-device-alerts.md)
- [Monitoring](https://docs.roboflow.com/deploy/device-manager/monitoring.md)
- [View a Stream](https://docs.roboflow.com/deploy/device-manager/monitoring/view-a-stream.md): Learn how to view a Stream configured with Deployment Manager.
- [View Device Logs](https://docs.roboflow.com/deploy/device-manager/monitoring/view-device-logs.md)
- [View Device Activity](https://docs.roboflow.com/deploy/device-manager/monitoring/view-device-activity.md)
- [View the Resource Monitor](https://docs.roboflow.com/deploy/device-manager/monitoring/view-the-resource-monitor.md)
- [View Event Store Status](https://docs.roboflow.com/deploy/device-manager/monitoring/view-event-store-status.md)
- [Making Changes](https://docs.roboflow.com/deploy/device-manager/making-changes.md)
- [Update Device Configuration](https://docs.roboflow.com/deploy/device-manager/making-changes/update-device-configuration.md)
- [Configure AI1 Camera Settings](https://docs.roboflow.com/deploy/device-manager/making-changes/configure-ai1-camera-settings.md)
- [Redeploy Deployment Manager](https://docs.roboflow.com/deploy/device-manager/making-changes/redeploy-deployment-manager.md)
- [API Keys for Device Manager](https://docs.roboflow.com/deploy/device-manager/making-changes/api-keys-for-device-manager.md)
- [Terminate a Stream](https://docs.roboflow.com/deploy/device-manager/making-changes/delete-a-stream.md)
- [Pause and Resume a Stream](https://docs.roboflow.com/deploy/device-manager/making-changes/stop-a-stream.md)
- [Trigger a Stream](https://docs.roboflow.com/deploy/device-manager/making-changes/trigger-a-stream.md): Run a Workflow on demand against the latest frame from a Triggered stream.
- [Soft Reset a PoE Port](https://docs.roboflow.com/deploy/device-manager/making-changes/soft-reset-poe-port.md)
- [Configure Device Network](https://docs.roboflow.com/deploy/device-manager/making-changes/configure-device-network.md)
- [Set a Static IP for a Camera](https://docs.roboflow.com/deploy/device-manager/making-changes/set-camera-static-ip.md)
- [Delete a Device](https://docs.roboflow.com/deploy/device-manager/making-changes/delete-a-device.md)
- [PLC Relay](https://docs.roboflow.com/deploy/device-manager/plc-relay.md): Configure PLC Relay to read and write PLC tags over Allen-Bradley, Modbus TCP, or Siemens S7.
- [Active Learning](https://docs.roboflow.com/deploy/active-learning.md): Collect production inference data to continuously improve your model through review and retraining.
- [Model Monitoring](https://docs.roboflow.com/deploy/model-monitoring.md): A guide to Model Monitoring with Roboflow.
- [Alerting](https://docs.roboflow.com/deploy/model-monitoring/alerting.md)
- [Vision Events](https://docs.roboflow.com/deploy/vision-events.md): Record, search, and analyze what your deployed computer vision models see in production.
- [Use Cases](https://docs.roboflow.com/deploy/vision-events/use-cases.md): Group Vision Events by purpose using Use Cases.
- [Send Events](https://docs.roboflow.com/deploy/vision-events/send-events.md): Three ways to send Vision Events from your deployed models.
- [Query Events](https://docs.roboflow.com/deploy/vision-events/query-events.md): Search, filter, and browse Vision Events in the dashboard and via the API
- [Delete Events](https://docs.roboflow.com/deploy/vision-events/delete-events.md): Remove Vision Events from a Use Case through the dashboard or the API.
- [Operator Feedback](https://docs.roboflow.com/deploy/vision-events/operator-feedback.md): Let operators review Vision Events and mark them as correct, incorrect, or inconclusive.
- [Add Images for Training](https://docs.roboflow.com/deploy/vision-events/add-images-for-training.md): Send images from Vision Events into a Roboflow project for training.