FP32 Performance (Single-precision GFLOPS)

The theoretical computing power of the graphics card with single precision (32 bit) in GFLOPS. GFLOPS indicates how many trillion FP32 floating point operations the graphics card (GPU) can perform per second. The larger this number, the faster the graphics card is.

FP32 or "single precision" is a term for a floating point format which occupies 32 bits in computer memory and has a precision between 7 and 8 valid digits. It is laid down in the "IEEE 754" standard and defines how binary data are stored. The calculation according to FP32 is e.g. more complex than according to FP16 (half accuracy).

The FP32 raw performance is of a purely theoretical nature, as it is only a small part of a complex GPU. In addition to the memory equipment (graphics memory), the memory bandwidth or the memory rate also play a major role. The number of execution units is also an important indicator. Modern graphics cards are also very optimized and have different areas for different computing tasks, e.g. for calculating ML (machine learning) or image processing. Ray tracing cores also fall into this area.

However, the performance information does give an initial assessment of the expected performance of a graphics card. Since the FP32 performance can also be determined quite easily from game consoles (e.g. XBox Series X / S or Playstation 5) or internal processor graphics cards (iGPUs), the FP32 performance also enables a cross-system performance assessment.

Thanks to the manufacturer's FP32 performance information, it is also possible to compare graphics cards for which there are no precise benchmarks from games or specific applications. The raw performance is also hardly susceptible to future firmware or driver updates, which can significantly affect the performance values ??in games, for example.

FP32 (GFLOPS)

Apple iPad Pro 11" 3rd Gen Wi-Fi (2021)
Apple M1 @ 0.60 GHz
2,600.000
Apple iPad Air 10.9" 5th Gen Wi-Fi (2022)
Apple M1 @ 0.60 GHz
2,600.000
Apple iPad Air 10.9" 5th Gen Wi-Fi / Cellular (2022)
Apple M1 @ 0.60 GHz
2,600.000
Apple iPad Pro 11" 3rd Gen Wi-Fi / Cellular (2021)
Apple M1 @ 0.60 GHz
2,600.000
Apple iPad Pro 12.9" 5th Gen Wi-Fi / Cellular (2021)
Apple M1 @ 0.60 GHz
2,600.000
Apple iPad Pro 12.9" 5th Gen Wi-Fi (2021)
Apple M1 @ 0.60 GHz
2,600.000
Samsung Galaxy S22+ (Snapdragon)
Qualcomm Snapdragon 8 Gen 1 @ 3.00 GHz
2,236.000
Samsung Galaxy S22 Ultra (Snapdragon)
Qualcomm Snapdragon 8 Gen 1 @ 3.00 GHz
2,236.000
Samsung Galaxy S22 (Snapdragon)
Qualcomm Snapdragon 8 Gen 1 @ 3.00 GHz
2,236.000
Apple iPhone 15 Pro Max
Apple A17 Pro @ 3.78 GHz
2,147.000
Apple iPhone 15 Pro
Apple A17 Pro @ 3.78 GHz
2,147.000
Apple iPhone 15 Plus
Apple A16 Bionic @ 3.46 GHz
1,790.000
Apple iPhone 14 Pro Max
Apple A16 Bionic @ 3.46 GHz
1,789.000
Apple iPhone 15
Apple A16 Bionic @ 3.46 GHz
1,789.000
Apple iPhone 14 Pro
Apple A16 Bionic @ 3.46 GHz
1,789.000
Apple iPhone 14
Apple A15 Bionic (5-GPU) @ 3.23 GHz
1,500.000
Apple iPhone 14 Plus
Apple A15 Bionic (5-GPU) @ 3.23 GHz
1,500.000
Apple iPhone 13 Pro 6.1"
Apple A15 Bionic (5-GPU) @ 3.23 GHz
1,500.000
Apple iPad mini 8.3" 6th Gen Wi-Fi / Cellular (2021)
Apple A15 Bionic (5-GPU) @ 3.23 GHz
1,500.000
Apple iPad mini 8.3" 6th Gen Wi-Fi (2021)
Apple A15 Bionic (5-GPU) @ 3.23 GHz
1,500.000
Apple iPhone 13 Pro Max
Apple A15 Bionic (5-GPU) @ 3.23 GHz
1,500.000
Apple iPhone 13 Mini
Apple A15 Bionic (4-GPU) @ 3.23 GHz
1,200.000
Apple iPhone 13 6.1"
Apple A15 Bionic (4-GPU) @ 3.23 GHz
1,200.000
Apple iPhone SE 3rd Gen
Apple A15 Bionic (4-GPU) @ 3.23 GHz
1,200.000
Apple iPad Pro 11" 2nd Gen Wi-Fi / Cellular (2020)
Apple A12Z Bionic @ 2.49 GHz
1,110.000
Apple iPad Pro 11" 2nd Gen Wi-Fi (2020)
Apple A12Z Bionic @ 2.49 GHz
1,110.000
Apple iPad Pro 12.9" 4th Gen Wi-Fi / Cellular (2020)
Apple A12Z Bionic @ 2.49 GHz
1,110.000
Apple iPad Pro 12.9" 4th Gen Wi-Fi (2020)
Apple A12Z Bionic @ 2.49 GHz
1,110.000
Apple iPhone 12 mini 5.4"
Apple A14 Bionic @ 3.00 GHz
749.000







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