docs/en/platform/deploy/index.md
Ultralytics Platform provides comprehensive model deployment options for putting your YOLO models into production. Test models with browser-based inference, deploy to dedicated endpoints across 42 global regions, and monitor performance in real-time.
<p align="center"> <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/JjgQYPetX8w" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen> </iframe><strong>Watch:</strong> Get Started with Ultralytics Platform - Deploy
</p>The Deployment section helps you:
Predict tab<!-- screenshot -->
Ultralytics Platform offers multiple deployment paths:
| Option | Description | Best For |
|---|---|---|
| Predict Tab | Browser-based inference with image, webcam, and examples | Development, validation |
| Shared Inference | Multi-tenant service across 3 regions | Light usage, testing |
| Dedicated Endpoints | Single-tenant services across 42 regions | Production, low latency |
graph LR
A[✅ Test]:::start --> B[⚙️ Configure]:::proc
B --> C[🌐 Deploy]:::proc
C --> D[📊 Monitor]:::out
classDef start fill:#4CAF50,color:#fff
classDef proc fill:#2196F3,color:#fff
classDef out fill:#9C27B0,color:#fff
| Stage | Description |
|---|---|
| Test | Validate model with the Predict tab |
| Configure | Select a region and review the editable, auto-generated deployment name |
| Deploy | Create a dedicated endpoint from the Deploy tab |
| Monitor | Track requests, latency, errors, and logs in Monitoring |
The shared inference service runs in 3 key regions, automatically routing requests based on your data region:
graph TB
User[User Request]:::start --> API[Platform API]:::proc
API --> Router{Region Router}:::decide
Router -->|US users| US["US Predict Service
Iowa"]:::out
Router -->|EU users| EU["EU Predict Service
Belgium"]:::out
Router -->|AP users| AP["AP Predict Service
Taiwan"]:::out
classDef start fill:#4CAF50,color:#fff
classDef proc fill:#2196F3,color:#fff
classDef decide fill:#FF9800,color:#fff
classDef out fill:#9C27B0,color:#fff
{% include "macros/platform-data-regions.md" %}
Deploy to 42 regions worldwide on Ultralytics Cloud:
Each endpoint is a single-tenant service with:
1 CPU, 2 GiB memory, minInstances=0, maxInstances=1Access the global deployments page from the sidebar under Deploy. This page shows:
<!-- screenshot --> !!! info "Automatic Polling"
The page polls every 15 seconds normally. When deployments are in a transitional state (`creating`, `deploying`, or `stopping`), polling increases to every 3 seconds for faster feedback.
Deploy close to your users with 42 regions covering:
Endpoints currently behave as follows:
minInstances defaults to 0maxInstances is currently capped at 1 on all plansUse the measured region latency to place an endpoint near its callers. Actual inference latency depends on the model, input size, endpoint state, and network path.
Each running deployment includes an automatic health check with:
Create a deployment:
!!! example "Quick Deploy"
```text
Model → Deploy tab → Select region → Click Deploy → Endpoint URL ready
```
Once deployed, use the endpoint URL with your API key to send inference requests from any application.
| Feature | Shared | Dedicated |
|---|---|---|
| Service | Shared across Platform users | Dedicated to one deployment |
| Scale | Managed by Platform | Scale-to-zero, one instance |
| Regions | 3 data regions | Choose from 42 deployment regions |
| URL | Platform model API | Generated deployment endpoint URL |
| Testing | Model Predict tab | Deployment-card Predict tab or API |
The deployment remains in a creating or deploying state while its service starts. It becomes usable when the status changes to Ready; timing varies by model and region.
Yes, each model can have multiple endpoints in different regions. Deployment counts are limited by plan: Free 3, Pro 10, Enterprise unlimited.
With scale-to-zero enabled:
First requests after an idle period trigger a cold start.