Google is working to bring its Gemini AI features to mid-range and budget smartphones through a new chipset designed to handle on-device artificial intelligence processing at lower cost.
The move would extend capabilities previously confined to high-end devices — such as the Pixel 9 series — to a broader segment of the Android market.
What Is On-Device AI
On-device AI refers to machine learning tasks processed directly on a phone’s chip rather than routed through remote servers. It allows features like live translation, photo editing, and voice recognition to work faster and without an internet connection.
Until now, those tasks have required the processing power of premium chips, keeping them out of reach for phones priced below roughly $500.
The Chipset Question
Google’s strategy centers on optimizing Gemini Nano — the smallest and most efficient version of its Gemini model — to run on less powerful silicon.
Gemini Nano already runs on select mid-tier devices, but full Gemini Intelligence features, which bundle multiple AI tools into a unified system, have remained exclusive to flagship hardware.
A new chipset tier, built with tighter AI-processing efficiency in mind, could change that calculus.
Qualcomm and MediaTek both supply chipsets across multiple price bands. Either could serve as the delivery mechanism for expanded Gemini support, though Google has not publicly named a specific silicon partner for this initiative.
Android’s Market Breakdown
The stakes are significant. Devices priced under $400 represent the majority of global Android shipments.
According to IDC, smartphones priced below $400 accounted for roughly 60 percent of total global smartphone shipments in 2023. That segment is concentrated in emerging markets across South Asia, Southeast Asia, Latin America, and sub-Saharan Africa.
Google has a strategic interest in seeding those markets with AI-enabled devices, both to grow its assistant ecosystem and to compete with Chinese manufacturers who bundle their own AI features into affordable handsets.
Gemini’s Current Reach
Google launched Gemini Nano on the Pixel 8 series in late 2023, marking the first time an on-device large language model shipped on a consumer Android phone.
Since then, it has expanded Gemini integrations to Samsung’s Galaxy S24 line and select other premium devices running Qualcomm’s Snapdragon 8 Gen 3 or equivalent processors.
The full Gemini Intelligence suite — which includes AI-assisted summarization, image description, and contextual suggestions across apps — currently requires either a Tensor G4 chip or top-tier third-party silicon.
Developer and Carrier Pressure
Developers have pushed Google to lower the hardware bar for Gemini APIs (application programming interfaces, the tools developers use to embed AI into apps).
A wider hardware base would let app makers target AI-enabled features at a larger share of their user base without building separate versions of their software.
Carriers in price-sensitive markets have made similar requests, arguing that AI exclusivity to flagship devices slows adoption of newer Android builds across their networks.
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