For this edition of Chip Battle, we are pitting Samsung’s Exynos 7904 chipset against Qualcomm’s Snapdragon 675 processor. Both chipsets are found in mid-range phones, though the former is limited to just Samsung phones while Qualcomm‘s chipset appears in phones from various brands. Let’s dive in and see how which chipset comes out on top.
Node
The Exynos 7904 is a 14nm processor while the Snapdragon 675 is an 11nm processor. A smaller node size means the processor is more power-efficient; and in this case, the Snapdragon 675 is the one with the smaller node size.
CPU
Samsung’s processor has eight cores in a 2+6 configuration. There are two Cortex-A73 performance cores clocked at 1.8GHz while the other six cores are Cortex-A53 cores clocked at 1.6GHz.
The Snapdragon 675 has eight custom Kryo 460 cores which are actually two performance cores that are based on the Cortex-A76 and clocked at 2.0GHz and six power-saving efficiency cores based on the Cortex-A55 clocked at 1.6GHz.
It is easy to see which chipset is more powerful. The Cortex-A76 cores are the successors to the A73 and so is the relationship between the Cortex-A55 and Cortex-A53. Not only are the cores of the Snapdragon 675 more powerful, but they are also clocked at higher speeds. The benchmark results below also confirm the Snapdragon 675 easily beats the Exynos 7904.
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GPU
There is an Adreno 612 GPU in the Snapdragon 675 while the Exynos 7904 has Arm’s Mali-G71 MP2 GPU. Benchmark results have shown the Adreno 612 is a more powerful GPU than the Mali G71 MP2, so this is another win for the Snapdragon 675.
Connectivity
The Exynos 7904 has an LTE Cat. 12 modem with speeds up to 600Mbps for downloads and 150Mbps for uploads. It also has support for dual-band Wi-Fi, Bluetooth 5.0. The Snapdragon X12 LTE modem inside the Snapdragon 675 offers the same downlink and uplink speeds too. It also has Bluetooth 5.0 and support for dual-band Wi-Fi.
Conclusion
The Snapdragon 675 is easily the winner here. It packs a better CPU as well as GPU compared to the Exynos 7904. It is also more efficient as a result of its smaller node size.
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