YOLO Vision 2026:

Deployment#

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.



Watch: Get Started with Ultralytics Platform - Deploy

Overview#

The Deployment section helps you:

  • Test models directly in the browser with the Predict tab
  • Deploy to dedicated endpoints in 42 global regions
  • Monitor request metrics, logs, and health checks
  • Scale to zero when idle (deployments currently run a single active instance)

Ultralytics Platform Deploy Page World Map With Overview Cards

Deployment Options#

Ultralytics Platform offers multiple deployment paths:

OptionDescriptionBest For
Predict TabBrowser-based inference with image, webcam, and examplesDevelopment, validation
Shared InferenceMulti-tenant service across 3 regionsLight usage, testing
Dedicated EndpointsSingle-tenant services across 42 regionsProduction, low latency

Workflow#

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
StageDescription
TestValidate model with the Predict tab
ConfigureSelect a region and review the editable, auto-generated deployment name
DeployCreate a dedicated endpoint from the Deploy tab
MonitorTrack requests, latency, errors, and logs in Monitoring

Architecture#

Shared Inference#

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<br/>Iowa"]:::out
    Router -->|EU users| EU["EU Predict Service<br/>Belgium"]:::out
    Router -->|AP users| AP["AP Predict Service<br/>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
RegionLabelLocationBest For
USAmericasIowa, USAAmericas users, fastest for Americas
EUEurope, Middle East & AfricaBelgium, EuropeEuropean users, GDPR compliance
APAsia PacificTaiwan, Asia-PacificAsia-Pacific users, lowest APAC latency

Dedicated Endpoints#

Deploy to 42 regions worldwide on Ultralytics Cloud:

  • Americas: 14 regions
  • Europe: 13 regions
  • Asia-Pacific: 12 regions
  • Middle East & Africa: 3 regions

Each endpoint is a single-tenant service with:

  • Default resources of 1 CPU, 2 GiB memory, minInstances=0, maxInstances=1
  • Scale-to-zero when idle
  • Unique endpoint URL
  • Independent monitoring, logs, and health checks

Deployments Page#

Access the global deployments page from the sidebar under Deploy. This page shows:

  • World map with deployed region pins (interactive map)
  • Overview cards: Total Requests (24h), Active Deployments, Error Rate (24h), P95 Latency (24h)
  • Deployments list with three view modes: cards, compact, and table
  • New Deployment button to create endpoints from any completed model

Ultralytics Platform Deploy Page Overview Cards And Deployments List

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.

Key Features#

Global Coverage#

Deploy close to your users with 42 regions covering:

  • North America, South America
  • Europe, Middle East, Africa
  • Asia Pacific, Oceania

Scaling Behavior#

Endpoints currently behave as follows:

  • Scale to zero: minInstances defaults to 0
  • Single active instance: maxInstances is currently capped at 1 on all plans

Regional Deployment#

Use 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.

Health Checks#

Each running deployment includes an automatic health check with:

  • Live status indicator (healthy/unhealthy)
  • Response latency display
  • Auto-retry when unhealthy (polls every 20 seconds)
  • Manual refresh button

Quick Start#

Create a deployment:

  1. Train or upload a model to a project
  2. Go to the model's Deploy tab
  3. Select a region from the latency table
  4. Click Deploy and wait for the deployment status to become Ready
Quick Deploy
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.

FAQ#

What's the difference between shared and dedicated inference?#

FeatureSharedDedicated
ServiceShared across Platform usersDedicated to one deployment
ScaleManaged by PlatformScale-to-zero, one instance
Regions3 data regionsChoose from 42 deployment regions
URLPlatform model APIGenerated deployment endpoint URL
TestingModel Predict tabDeployment-card Predict tab or API

How long does deployment take?#

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.

Can I deploy multiple models?#

Yes, each model can have multiple endpoints in different regions. Deployment counts are limited by plan: Free 3, Pro 10, Enterprise unlimited.

What happens when an endpoint is idle?#

With scale-to-zero enabled:

  • Endpoint scales down after inactivity
  • First request triggers cold start
  • Subsequent requests are fast

First requests after an idle period trigger a cold start.

Contributors
GLglenn-jocher16RAraimbekovm1RIRizwanMunawar1SEsergiuwaxmann1

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