Steve Jobs here, had to come back from the dead for this.
Within 5 years Qualcomm will give away its patents for free and beg customers to
use their chips. LOL
https://www.theverge.com/2018/8/31/17803682/huawei-kirin-980-processor-soc-qualcomm-snapdragon-845-ifa-2018
But the product that Huawei really wants to compare the Kirin 980 against is Qualcomm’s Snapdragon 845, the chip that figures in practically every Android flagship phone not made by Huawei. It’s worth noting that the 845 has been out for many months now whereas Huawei’s 980 won’t be in any retail devices until next month at the earliest (Huawei let slip that it’s planning its Mate 20 announcement for October 16th). Still, the margin of improvement that Huawei is quoting over its major rival is impressive.
On the memory front, Huawei says the Kirin 980 has 20 percent better bandwidth and 22 percent lower latency than the Snapdragon 845. In practical terms, that means faster app launches across the full range of the world’s most popular apps. In gaming applications, the 980 has been shown to produce 22 percent higher frame rates than the 845, and its power consumption when gaming is said to be 32 percent lower.
Photography performance is another major upgrade for the Kirin chip, according to Huawei’s numbers. Using a new dual ISP (image signal processor), the Kirin 980 is 46 percent faster at camera processing than its predecessor, with a related 23 percent improvement in power efficiency while recording, and 33 percent improvement in latency.
HUAWEI’S CHIP DESIGNS PUT AN EMPHASIS ON ACCELERATING AI PROCESSING
Huawei has doubled down on its AI processing aspirations, adding a dual NPU (neural processor unit) to the Kirin 980, which performs AI-assisted image recognition tasks at a rate of 4,500 images per minute. By the same measure, the Snapdragon 845 reaches 2,371 and Apple’s A11, which enjoys performance leads in other categories, gets only 1,458. AI also aids the Kirin 980’s power efficiency, as Huawei says it’s using it to more accurately and intelligently predict load requirements, making it more responsive to the power needs of the user — both when the chip needs to power up more cores and when it’s done its task and can save energy by slowing down.