Tesla Supercharger Predictions Now Live on Google Maps

Background: A Two-Phase Google Maps Integration

Phase 1 — Live Availability (November 2025)

On November 11–12, 2025, Tesla opened its API to Google Maps for the first time, enabling live Supercharger stall availability data in Google Maps . This gave all EV drivers—not just Tesla owners—real-time visibility into how many stalls were open at any given moment across North America and Europe . It marked a major expansion after years of Tesla keeping that data exclusive to its own ecosystem .

Phase 2 — Forecasted Availability (June 2026)

The new forecasted availability goes a step further: it uses Tesla's data modeling to show the expected number of open stalls at the time of arrival . This solves the problem Google itself described in November 2025: "While Maps already shows you if a charger is available right now… it could be in use by the time you get there" .

How the New Predictions Differ from Google's Own EV Charger Predictions

Google's own EV charger predictions, rolled out in November 2025 for networks like Electrify America, are based on Google's general crowd-sourced and historical data models . In contrast, Tesla's forecasted availability is powered by Tesla's own machine learning model, trained on 9 million miles of aggregated, anonymized vehicle trajectory data collected within Supercharger geofences worldwide—vastly richer and more precise data for Tesla stations specifically .

A History of Predictive Features in Tesla's Native Navigation

Tesla's native navigation has included predictive elements for years:

• Automatic Navigation – Tesla vehicles can predict a destination and auto-initiate navigation based on commonly driven routes, time of day, and calendar entries .
• Live Stall Availability (Native UI) – Tesla introduced live Supercharger stall availability in its in-car navigation and app as early as 2017, showing real-time occupancy per stall .
• 3D Site Map (March 2026) – Tesla deployed a 3D Supercharger site map showing live occupancy status (Available, Occupied, or Down) for every individual stall at supported stations .

Machine Learning Model Improvements (April 2026)

In April 2026, Tesla deployed an updated machine learning model across its Supercharger network specifically to improve wait-time and availability predictions . Key details:

• Training data: 9 million miles of aggregated, anonymized vehicle trajectory data from within charger geofences globally .
• Goal: Better identify which vehicles are actually coming to charge (vs. just passing through), so the system can predict queue lengths more accurately.
• Result: Queue length estimation error reduced to approximately 20%, allowing Tesla to predict wait times and availability at stations significantly more reliably than before .

Growing Demand and Network Expansion Context

Accurate predictions have become increasingly critical as Supercharger demand surges:

• Record Q1 2026 charging sessions: Supercharging sessions increased 26% year-over-year to 53 million sessions in Q1 2026 alone .
• Network milestone: The Supercharger network crossed 80,000 global stalls in Q1 2026, with 80,018 stalls at 8,502 sites as of April 1, 2026 .
• Q1 2026 expansion: Tesla added 2,500 new stalls globally (a 19% year-over-year increase) and opened 310 new Supercharger sites in just three months .
• End of the V3 era: On March 16, 2026, Gigafactory New York produced its last V3 Supercharger cabinet; all new installations now use V4 hardware .
• Europe detail: As of April 10, 2026, Europe had approximately 14,200 stalls across 1,100+ sites, with 5,008 V4 stalls (35% of the total) across 412 V4 stations .

The combination of record demand, rapid V4 expansion, and the new ML-powered forecast feature aims to reduce range anxiety and queue frustration for the growing number of EV drivers relying on the Supercharger network.