samsung SM-S938U1 vs iPhone 16 Pro
| samsung SM-S938U1 | iPhone 16 Pro | Difference | |
|---|---|---|---|
| Single Precision | 596 | 4614 | 12.9% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Half Precision | 27402 | 7849 | 349.1% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Quantized | 61186 | 6258 | 977.7% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Geekbench AI 1.2.0 | Geekbench AI 1.2.0 | ||
System Information
| samsung SM-S938U1 | iPhone 16 Pro | |
|---|---|---|
| AI Framework | TensorFlow Lite | Core ML |
| AI Backend | QNN | CPU |
| AI Device | Qualcomm ARMv8 | Apple A18 Pro |
| Operating System | Android 15 | iOS 18.1.1 |
| Model | samsung SM-S938U1 | iPhone 16 Pro |
| Processor |
Qualcomm ARMv8 @ 3.53 GHz
1 Processor, 8 Cores |
Apple A18 Pro @ 4.04 GHz
1 Processor, 6 Cores |
| Processor ID | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 | ARM |
| Motherboard | sun | D93AP |
| Memory | 10.86 GB | 7.49 GB |
AI Performance
| samsung SM-S938U1 | iPhone 16 Pro | Difference | |
|---|---|---|---|
| Image Classification (SP) | 458 | 2032 | 22.5% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Image Classification (HP) | 21438 | 3385 | 633.3% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Image Classification (Q) | 49510 | 2281 | 2170.5% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Image Segmentation (SP) | 573 | 1999 | 28.7% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Image Segmentation (HP) | 13692 | 3018 | 453.7% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Image Segmentation (Q) | 41700 | 3388 | 1230.8% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Pose Estimation (SP) | 643 | 9164 | 7.0% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Pose Estimation (HP) | 123874 | 18729 | 661.4% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Pose Estimation (Q) | 478115 | 15932 | 3001.0% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Object Detection (SP) | 312 | 2143 | 14.6% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Object Detection (HP) | 18896 | 3844 | 491.6% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Object Detection (Q) | 21667 | 2687 | 806.4% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Face Detection (SP) | 810 | 3647 | 22.2% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Face Detection (HP) | 42171 | 7585 | 556.0% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Face Detection (Q) | 143874 | 4282 | 3360.0% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Depth Estimation (SP) | 785 | 8003 | 9.8% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Depth Estimation (HP) | 84045 | 14251 | 589.7% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Depth Estimation (Q) | 144875 | 9854 | 1470.2% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Style Transfer (SP) | 1263 | 24810 | 5.1% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Style Transfer (HP) | 98860 | 38039 | 259.9% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Style Transfer (Q) | 490962 | 31312 | 1568.0% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Image Super-Resolution (SP) | 343 | 5786 | 5.9% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Image Super-Resolution (HP) | 53817 | 6940 | 775.5% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Image Super-Resolution (Q) | 135068 | 4994 | 2704.6% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Text Classification (SP) | 460 | 3446 | 13.3% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Text Classification (HP) | 3914 | 5958 | 65.7% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Text Classification (Q) | 7946 | 5890 | 134.9% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Machine Translation (SP) | 851 | 3803 | 22.4% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Machine Translation (HP) | 4708 | 7102 | 66.3% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
| Machine Translation (Q) | 3131 | 7165 | 43.7% |
| samsung SM-S938U1 | |||
| iPhone 16 Pro | |||
