Skip to main content
  1. Home
  2. Computing
  3. News

Apple says users are snapping up Macs faster than ever and created a supply shortage

Add as a preferred source on Google
Apple MacBook Neo with users hands on it
Apple

Apple has a good problem on its hands: it simply cannot make enough Macs. On its fiscal Q2 2026 earnings call, CEO Tim Cook confirmed that demand for the Mac lineup has outpaced what the company can supply — and honestly, that’s not a sentence you’d have expected to write a few years ago when Mac growth was chugging along in iPhone’s shadow.

The culprits are interesting. The Mac Mini and Mac Studio are flying off the shelves, and Cook attributes a big chunk of that to people waking up to how capable Apple Silicon is for running AI tools and agentic workflows locally. That’s a trend the company apparently didn’t fully see coming. When your own CEO admits you “undercalled the demand,” that’s a genuine surprise.

The MacBook Neo effect is real

The MacBook Neo, Apple’s newer, more affordable laptop, has been blowing expectations out of the water. Schools are ditching Chromebooks for it, and first-time Mac buyers are coming in droves. The March quarter set a record for new Mac customers, which is exactly the kind of metric Apple has been chasing for years in a category that, let’s be honest, often felt like preaching to the converted.

Mac revenue hit $8.4 billion for the quarter, up 6% year-over-year despite the supply crunch — which means the real number, unconstrained, would have been even better. Cook warned that the Mini and Studio in particular could take several months to reach supply-demand balance. That’s not a one-quarter blip.

This isn’t just a sales spike

What makes this moment notable is the shift in how people are buying Macs. It’s no longer just creative professionals or developers. Enterprise teams are deploying them at scale for AI development. Public school districts are choosing them over budget Windows alternatives. Emerging markets like India are seeing double-digit Mac growth. The product is broadening its reach in a way that feels structural rather than just cyclical.

Apple has spent years arguing that its silicon advantage would eventually pull more people into the Mac ecosystem. It looks like that bet is finally paying off — faster than even Apple expected.

Shimul Sood
Shimul is a contributor at Digital Trends, with over five years of experience in the tech space.
The Mac Pro nearly received an M3 Extreme chip twice as powerful as M3 Ultra
High production costs likely killed Apple’s M3 Extreme plans
Apple's Mac Pro on a table at a press event.

Apple discontinued the Mac Pro earlier this year, ending a 20-year run for a computer that once represented the very best of the company’s desktop lineup. However, Apple reportedly had much bigger plans for the machine before ultimately replacing it with the Mac Studio.

According to Bloomberg’s Mark Gurman, Apple developed an M3 Extreme chip that could have offered twice as many CPU and GPU cores as the M3 Ultra. The processor was intended to sit above the Ultra tier and could have finally given the Mac Pro the performance advantage it badly needed. Apple eventually abandoned the chip due to concerns over production costs and limited demand for such an expensive machine.

Read more
Hidden prompts can secretly rewrite an AI’s memory, and researchers say that’s a serious problem
Researchers discover AI attack that rewrites an assistant's long-term memory
Chatbot on a smartphone.

Large language models are getting better at remembering us. Whether it's your preferred writing style, recurring tasks, shopping habits or project deadlines, AI assistants are increasingly storing long-term memories to make future conversations feel more personal and useful. But according to new research, that same feature could become one of AI's biggest security vulnerabilities.

Researchers from New Mexico State University have demonstrated a new attack called GhostWriter, capable of secretly planting false memories inside AI agents. Rather than stealing information outright, the attack manipulates what an AI remembers, potentially causing it to make dangerous decisions long after the original attack has taken place.

Read more
This experiment shows how easy it is to poison an open-weight AI model for under $100
This research raises new doubts about trusting open weight AI models.
Computer, Electronics, Laptop

Open-weight AI models have been having a moment lately. Just this month, Moonshot's massive Kimi K3 model landed close behind Claude Fable 5 and GPT 5.6 Sol in several benchmarks, all while remaining fully open-weight and downloadable by anyone.

However, Katie Paxton-Fear, a cybersecurity lecturer at Manchester Metropolitan University and staff security advocate at Semgrep, managed to poison an open-weight model and proved how easily that openness can be turned against you (via The Register).

Read more