k
keynews.ai
keynews.ai
ChipsThe story, in brief

Qualcomm launches two new smartphone chips with emphasis on AI

Qualcomm's new flagship chip runs a 30B MoE model locally — on-device AI just got real for smartphones.

Reporting by TechCrunch AI 1 min brief
Paper-cut illustration of an amber microchip with circuit paths extending into a row of data-center cabinets.
The infrastructure powering AI.AI illustration by KeyNews
The KeyNews take

Why it matters

On-device AI capability in smartphones is crossing a meaningful threshold. Practitioners building mobile-first AI products now have hardware that can run substantial models without cloud dependency; this reshapes edge AI economics and privacy-by-design strategies.

The key facts

8 to know

  1. Qualcomm launched two new smartphone chips

  2. Top chip can run 30B mixture-of-experts model locally

  3. On-device inference capability milestone for mobile processors

  4. Published September 22, 2026

  5. Qualcomm launches two new smartphone chips

  6. Top chip can run 30B mixture-of-experts models locally

  7. Emphasis on on-device AI inference

  8. Published Sep 22, 2026

Go to the source

TechCrunch AItechcrunch.com

Publisher excerpt: Qualcomm said that its new top chip can run 30B mixture-of-expert model locally.
Read original report
Back to today's editionMore chips news

The wider picture

View all
Paper-cut illustration of an amber microchip with circuit paths extending into a row of data-center cabinets.
AI illustration by KeyNews
Chips01

Qualcomm releases Android chip built for AI as memory shortage weighs on smartphone market

Qualcomm is positioning on-device AI as a differentiation play amid smartphone market headwinds. The chip release signals how AI is reshaping mobile silicon strategy — but the broader market contraction undercuts the addressable opportunity.

CNBC Technology
Paper-cut illustration of an amber microchip with circuit paths extending into a row of data-center cabinets.
AI illustration by KeyNews
Chips02

Why confidential computing is essential for enterprise AI

As enterprises push AI into sensitive domains (healthcare, finance, government), protecting data during processing — not just at rest or in transit — is shifting from a nice-to-have security feature to a prerequisite for deployment. HPE and NVIDIA are positioning confidential computing as foundational infrastructure for sovereign AI.

CIO
Paper-cut illustration of an amber microchip with circuit paths extending into a row of data-center cabinets.
AI illustration by KeyNews
Chips03

Beyond the limits of air: Why liquid cooling is becoming a strategic imperative for AI

Liquid cooling is shifting from niche to strategic necessity as GPU power density explodes. For practitioners building or deploying AI at scale, this isn't optional—it's a 18–24 month ROI play that unlocks denser racks, lower OpEx, and competitive advantage. The buildout architecture is changing.

CIO