Woot is now offering a chance to save on Apple’s 13-inch M1 MacBook Air with some extra memory built in. We really only ever see discounts on the baseline configuration for Apple’s most affordable MacBook. And now for those who still want that more wallet-friendly price but with a little extra performance, we have you covered. The 256GB model with an elevated 16GB of RAM now clocks in at $849.99 Prime shipped, with delivery running you $6 otherwise. It’s down from the usual $1,199 price tag while delivering the best price of the year at $349 off. Get a better idea of its performance in our hands-on review, and then head below for more.
While it isn’t that all-new version of Apple’s most portable MacBook, there is still something to be said for just how good of a value the original M1 MacBook Air still is, especially with as steep of a discount attached as you’ll find. Centered around a 13-inch Retina display with Apple Silicon under the hood, there’s also a pair of Thunderbolt ports supplemented by Wi-Fi 6 as well as 256GB of storage and an elevated 16GB of RAM. This makes for a far more capable machine than the usual discounts we see on the baseline model, offering double the RAM.
If you’re looking for more insight on why the M1 MacBook Air is worth considering over its newer M2 counterpart, we took a more in-depth look at how the two stack up over on 9to5Mac. Despite all of the love and fanfare around the newer version, our main takeaway was just how compelling the M1 MacBook Air still is for most users, especially those who want a more affordable package that’s even more portable than its predecessor.
It’s iPhone event week, and all of the other best deals are now up for grabs in our Apple guide.
Apple 13-inch M1 MacBook Air features:
The Apple 13″ MacBook Air features Apple’s first chip designed specifically for Mac. The Apple M1 integrates the CPU, GPU, Neural Engine, I/O, and more into a single system on a chip (SoC). Tackle your projects with the fast 8-Core CPU and take on graphics-intensive apps and games with the 8-core GPU. Accelerate machine learning tasks with the 16-core Neural Engine.
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