Qualcomm CEO says AI firms want 100B-parameter models running on phones by 2028

Your phone may be headed for a much more demanding job description. Qualcomm CEO Cristiano Amon says AI companies are already asking for smartphones that can run 100-billion-parameter models continuously by 2028.

Amon made the comments in an interview on October 8, 2026. He described a shift toward always-on “agentic” AI, meaning software that acts on your behalf rather than waiting for you to tap an app.

What AI companies are asking for

According to Amon, the models AI firms want would operate with personal context. They would understand what a user intends, reason through the request, and plan actions on their own.

The scale of the request becomes clearer next to what Qualcomm just shipped. At its Snapdragon Summit on September 22, 2026, the company unveiled the Snapdragon 8 Elite Gen 6 and Extreme Gen 6 platforms.

Those chips, built on 2nm technology, are designed to run mixture-of-experts models of up to 30 billion parameters directly on the device. Going from 30 billion to 100 billion is more than a threefold jump, inside the same rough physical footprint of a phone.

How Qualcomm is squeezing big models into small devices

Qualcomm is leaning on several techniques to make the math work. One involves loading model parameters from flash storage, so the full model does not need to sit in active memory all at once.

The new platforms also expand the memory available to the Neural Processing Unit, the part of the chip dedicated to AI workloads. Qualcomm also pointed to intelligent flash management and a low-power memory architecture as ways to support larger models.

Then there are always-on sensing hubs. These run much smaller models, at approximately 200 million parameters, continuously in the background. Qualcomm says its new chips can process approximately 1 million tokens per day, tokens being the chunks of text a model reads and writes.

Why the phone still matters

Amon has been consistent on one point: the smartphone is not going anywhere. He argued that phones will remain the central hub for personal AI, since they hold the context about a person’s life that makes an assistant useful.

Amon tied the AI push directly to hardware demand. He linked anticipated growth in smartphone sales to these capabilities, noting that rising memory prices have held back users from upgrading.

Qualcomm is not alone in eyeing this timeline. OpenAI is reportedly also exploring hardware aimed at similar AI capabilities by 2028, though firm details have not been disclosed.

What this means for the industry

The case for on-device AI rests on three advantages over cloud-dependent systems: privacy, lower latency, and better power efficiency. Data that never leaves your phone cannot leak from someone else’s server, and answers do not have to make a round trip across the internet.

The risks are real, though. Reaching 100-billion-parameter models on a phone is a multi-year engineering challenge, and the 2028 target reflects what AI companies are asking for, not a product anyone has promised to deliver.

Memory pricing is the obvious pressure point. If costs stay elevated, the hardware needed for these models could push phone prices higher at the exact moment the industry hopes to lure buyers back.

Battery life is the other question hanging over “continuously.” A model that runs all day has to do so without draining the phone by lunchtime, which is why Qualcomm keeps emphasizing low-power architecture and small background models.

The things to watch are fairly concrete. Track how quickly on-device model sizes climb from the 30 billion Qualcomm supports today, whether memory prices ease, and whether OpenAI or other AI firms put real hardware details on the table before 2028.