Nvidia and Nokia Put the First AI-RAN Call on a Live Network

Nvidia, Nokia and T-Mobile completed an AI-RAN call on a commercial network, a technical milestone for shared telecom and AI infrastructure that still lacks disclosed revenue.
Nvidia, Nokia and T-Mobile have completed what they describe as the first AI-RAN call on a live commercial network. The call used commercial ARC servers, Nokia’s CUDA-accelerated radio software and radios connected to T-Mobile’s existing 5G standalone core and a standard smartphone.
AI-RAN combines radio-access-network functions with accelerated computing on shared infrastructure. In principle, a carrier could use the same distributed hardware to run mobile-network workloads and low-latency AI applications. That could improve utilization at cell sites and metro facilities, but the economics depend on how much compute is available after network obligations and whether customers will pay for edge services.
Nvidia CEO Jensen Huang framed the opportunity at GTC Berlin as roughly 100,000 telecom sites representing about 100 gigawatts of distributed capacity. That is a vision of the addressable infrastructure, not a forecast of contracted AI demand or revenue. Nvidia said nearly 20 operators have announced AI-RAN collaborations, while commercial services are targeted for 2027.
BT, Deutsche Telekom and Elisa have announced pilots on Nokia software, with BT and Deutsche Telekom planning field trials in 2027. Those projects broaden the evidence beyond one U.S. call, but they remain tests rather than production-scale deployments.
The strategic appeal differs by company. Nvidia can sell accelerated computing, Nokia can embed its radio software in a new architecture, and carriers may gain a platform for edge inference. The risk is that shared systems cost more than conventional network equipment before demand for local AI services is proven.
Field trials will reveal whether that utilization case works under live network load.
The milestone verifies that the stack can place a commercial phone call. It does not establish capacity economics, service-level reliability at scale or operator returns. Investors should look next for named commercial deployments, disclosed hardware volumes and evidence that AI workloads generate incremental carrier revenue rather than merely raising capital spending.
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