Qualcomm reveals Snapdragon C specs for budget laptops, and Intel could have a serious headache

Qualcomm aims to solve the main issue plaguing budget laptops – performance and battery life – with its new Snapdragon C Platform. Introduced in May, this entry-tier chip promises speed, long battery life, and AI capabilities typically absent from budget-friendly devices. Now, Qualcomm has revealed the specs for its latest chip, and if it performs as expected, Intel will face a significant challenge.

The heart of the platform is Qualcomm’s Kryo CPU, an 8-core unit capable of reaching 3.0 GHz. Compared to Intel’s N250 chip found in similar-priced laptops, Qualcomm claims the Snapdragon C delivers up to 67% faster performance on battery and 2.1x better power efficiency. These efficiency gains translate to a noticeable difference in daily tasks.

Streaming Netflix reportedly consumes 106% more power, a Teams audio call uses 99% less energy, and even idle apps draw 39% less juice. With a dedicated integrated Adreno GPU and Hexagon NPU for AI tasks, the laptop multitasks smartly without draining the battery by lunchtime. Qualcomm targets students, families, small businesses, and frontline workers – anyone seeking a reliable laptop without paying flagship prices.

"Students, families and small businesses need reliable, responsive devices that keep up with their everyday tasks, from browsing and productivity to streaming and video conferencing, at accessible price points," said Nitin Kumar, VP of Product Management at Qualcomm Technologies. While Windows on ARM has struggled with native app support, this has improved dramatically.

Now, the platform supports popular apps such as Chrome, Excel, Instagram, Spotify, and Zoom, ensuring a seamless transition for users. Major manufacturers like Acer, Asus, HP, and Lenovo are set to release Snapdragon C laptops soon, making a budget PC upgrade more appealing than ever. Meanwhile, Anthropic is experimenting with an invisible watermark for AI-generated text, using Claude to create a statistical pattern that can later be detected.