Nvidia says Max-Q gaming notebooks could be yours for $1,200
Nvidia's new processor technology brings serious power to super-thin gaming laptops, and you won't necessarily have to pay a fortune to get it.
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Nvidia's Max Q promises maximum efficiency and maximum performance.
Nvidia 's next best thing for fast, high-performance gaming could be yours for as little as $1,200 (that roughly converts to £937 or AU$1610).
The company unveiled its new Max-Q technology at Computex in Taipei this week, saying it will bring the "maximum performance at the maximum energy efficiency point" for gaming notebooks . With all that efficiency Max-Q will make things much, much thinner too.
Best of all, Nvidia says you won't have to break the bank to get those improvements. Speaking to a small media gathering in Taipei today, Nvidia CEO Jensen Huang said the technology would be "very well priced.
"My expectation is that gaming notebooks [with Max-Q] will have a range anywhere from $1,200 all the way to something north of $2,000," he said.
He acknowledged that Nvidia provides the technology, relying on manufacturer partners to deliver the final notebook product, and that pricing will depend on "the combination of the CPUs and GPUs, the resolution of the panel you use, how much memory you have."
Nvidia CEO Jensen Huang shows off ROG's Zephyrus gaming laptop, talking up the power of Max-Q technology.
Regardless, he expected pricing "along those lines." He was also "really expecting it to boost the notebook market."
We're already starting to see the tech on the Computex show floor: Huang showed off ROG's new Zephyrus gaming laptop, weighing in at 2.2 kilograms and measuring just 18 mm thick. With a GTX 1080 graphics card inside, Huang said the Zephyrus is capable of powerful VR and 4K gaming, with 60 percent higher performance than the PlayStation 4 Pro.
"Everything the PS4 Pro can do, this can do better," Huang said, before adding, "Of course I'm very strong, but I can hold this all day."
Check out the rest of CNET's Computex 2017 coverage here.
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