// PC GAMER — GAMING
Now we know the prices of the new RTX Spark laptops and they're as expensive as I'm sure you feared
The launch is coming on October 16, is your bank account prepared?
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It is the best of times, it is the worst of times to unveil a whole new line of agentic and local AI-focused laptops. The new RTX Spark laptop hardware is going into a slew of big name, big brand notebooks, with pre-orders opening up now and, with the level of unified memory necessarily inside them, the pricing is getting on for prohibitive.
But it was always going to be that way. These are laptops built for AI processing and they need a ton of memory, and AI is the big thing right now so we need laptops that are designed from the ground up to run the best local models beautifully. But we're also at a point where AI is the big thing right now and that has sucked up all the available memory manufacturing making producing new PC hardware uncomfortably expensive.
There's a certain ouroboros-like feeling around these new machines, where they're designed for a world that is specifically making systems like them harder to make and sell to normal humans without seven figure incomes.
The new machines come with two flavours of Nvidia N1X processor; either the 20-core, 6144 CUDA core'd design, or the 18-core, 5120 CUDA core version. And with those Arm-based SoCs, sporting Nvidia GPU components, you're getting varying levels of un-upgradeable, soldered-on unified memory, from 24 GB all the way up to 128 GB.
And, if we take the entry-level version of the new Microsoft Surface Ultra laptop as an example, that 24 GB config, with the 18-core N1X will run you about $2,600. With a 512 GB SSD inside it. That is a lot of money for an Arm-based laptop relying heavily on emulation—at least right now—with not a lot of internal hardware, especially when the noise around RTX Spark is about its utility as a local AI beast.
24 GB of unified memory, shared therefore between CPU and GPU, doesn't feel like it's going to be able to get you access to the best local models, and that 512 GB SSD isn't going to be able to house too many of them, either. This is a slightly apples vs oranges comparison, I'll grant you, but a laptop with an RTX 5070 Ti and 16 GB of RAM is going to have a greater pool of memory to draw from, and you can pick one of those up for around $1,000 less than the cost of the cheapest Surface Ultra today.
To be honest, I would find it really hard to make a case for the lowest-spec Sparks right now, even though I know local models are getting ever more efficient and capable within memory-restricted environments. But if I'm dropping serious money right now specifically on a laptop that's positioning itself as being designed for local AI compute, I want to know I've got a pool of memory that's going to be solid for its lifetime. And it needs to be because there is no upgrading that memory once you've configured your purchase.
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