With the iPhone 16 series, one thing remains consistent: all models benefit from TSMC’s second-generation 3nm process, ensuring performance gains across the board. However, Apple has likely employed chip binning—a common industry practice—to differentiate between the ‘Pro’ and ‘non-Pro’ variants. This strategy isn’t new for the tech giant, and it seems they’ve applied it again for this year’s lineup.
One GPU Core Sets the A18 and A18 Pro Apart, With Everything Else Remaining Aligned
Looking through the specs of the iPhone 16, 16 Plus, 16 Pro, and 16 Pro Max, you’ll notice that the A18 and A18 Pro share almost identical configurations. Both chips feature six CPU cores—two for performance and four for power efficiency—at clock speeds peaking at 4.04GHz, indicating no significant architectural changes. Additionally, both chips house a 16-core Neural Engine designed for AI tasks, including generative AI capabilities under Apple’s Intelligence initiative.
The primary distinction lies in the GPU. While the A18 Pro, powering the iPhone 16 Pro and Pro Max, comes with a 6-core GPU, the standard A18 in the non-Pro models has a 5-core GPU. This isn’t the first time Apple has applied this strategy—similar binning was seen with the A15 Bionic in the iPhone 13 series, where Pro models received a 5-core GPU, and non-Pro models were equipped with a 4-core version.
Historically, GPU core differences have translated to performance disparities, such as a 55% increase in graphics performance from the iPhone 12 Pro compared to the non-Pro models. While it remains to be seen how big the performance gap will be between the A18 and A18 Pro, chip binning likely played a role in mass-producing the A18 Pro.
Reusing Lower-Binned A18 Pro Chips for Cost Efficiency
Apple may have repurposed lower-binned A18 Pro chips as standard A18s to optimize production costs while still ensuring that the iPhone 16 and 16 Plus deliver solid performance. This method allows Apple to use chips that don’t meet the higher specs required for the Pro models while still delivering a highly capable product.
This approach is not unusual in the tech industry, where companies aim to balance production costs and performance by reusing existing chips with slight modifications.
By Andrej Kovacevic
Updated on 11th September 2024