samsung SM-S931B vs iPhone 16 Pro
| samsung SM-S931B | iPhone 16 Pro | Difference | |
|---|---|---|---|
| Single Precision | 2054 | 4638 | 44.3% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Half Precision | 1997 | 7846 | 25.5% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Quantized | 3121 | 6266 | 49.8% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Geekbench AI 1.2.0 | Geekbench AI 1.2.0 | ||
System Information
| samsung SM-S931B | iPhone 16 Pro | |
|---|---|---|
| AI Framework | TensorFlow Lite | Core ML |
| AI Backend | CPU | CPU |
| AI Device | Qualcomm ARMv8 | Apple A18 Pro |
| Operating System | Android 15 | iOS 18.3.1 |
| Model | samsung SM-S931B | 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 | 7.48 GB |
AI Performance
| samsung SM-S931B | iPhone 16 Pro | Difference | |
|---|---|---|---|
| Image Classification (SP) | 2016 | 2042 | 98.7% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Image Classification (HP) | 1958 | 3361 | 58.3% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Image Classification (Q) | 4358 | 2289 | 190.4% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Image Segmentation (SP) | 2409 | 1977 | 121.9% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Image Segmentation (HP) | 1147 | 2935 | 39.1% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Image Segmentation (Q) | 1311 | 3369 | 38.9% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Pose Estimation (SP) | 2726 | 9356 | 29.1% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Pose Estimation (HP) | 4371 | 18905 | 23.1% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Pose Estimation (Q) | 8736 | 15841 | 55.1% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Object Detection (SP) | 966 | 2191 | 44.1% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Object Detection (HP) | 805 | 3871 | 20.8% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Object Detection (Q) | 2696 | 2703 | 99.7% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Face Detection (SP) | 3223 | 3688 | 87.4% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Face Detection (HP) | 3493 | 7680 | 45.5% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Face Detection (Q) | 6626 | 4302 | 154.0% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Depth Estimation (SP) | 3258 | 8026 | 40.6% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Depth Estimation (HP) | 4133 | 14414 | 28.7% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Depth Estimation (Q) | 8442 | 10007 | 84.4% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Style Transfer (SP) | 9158 | 24786 | 36.9% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Style Transfer (HP) | 7529 | 37912 | 19.9% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Style Transfer (Q) | 14312 | 31242 | 45.8% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Image Super-Resolution (SP) | 1458 | 5777 | 25.2% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Image Super-Resolution (HP) | 1665 | 6973 | 23.9% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Image Super-Resolution (Q) | 3601 | 4992 | 72.1% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Text Classification (SP) | 550 | 3421 | 16.1% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Text Classification (HP) | 550 | 5893 | 9.3% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Text Classification (Q) | 661 | 5887 | 11.2% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Machine Translation (SP) | 1361 | 3839 | 35.5% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Machine Translation (HP) | 1285 | 7104 | 18.1% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
| Machine Translation (Q) | 342 | 7154 | 4.8% |
| samsung SM-S931B | |||
| iPhone 16 Pro | |||
