realme RMX3300 vs samsung SM-F966U1
| realme RMX3300 | samsung SM-F966U1 | Difference | |
|---|---|---|---|
| Single Precision | 642 | 1765 | 36.4% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Half Precision | 889 | 2702 | 32.9% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Quantized | 882 | 2224 | 39.7% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Geekbench AI 1.2.0 | Geekbench AI 1.4.0 | ||
System Information
| realme RMX3300 | samsung SM-F966U1 | |
|---|---|---|
| AI Framework | TensorFlow Lite | TensorFlow Lite |
| AI Backend | GPU | GPU |
| AI Device | ARM ARMv8 | Qualcomm ARMv8 |
| Operating System | Android 14 | Android 16 |
| Model | realme RMX3300 | samsung SM-F966U1 |
| Processor |
ARM ARMv8 @ 1.78 GHz
1 Processor, 8 Cores |
Qualcomm ARMv8 @ 3.53 GHz
1 Processor, 8 Cores |
| Processor ID | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Motherboard | taro | sun |
| Memory | 10.95 GB | 14.75 GB |
AI Performance
| realme RMX3300 | samsung SM-F966U1 | Difference | |
|---|---|---|---|
| Image Classification (SP) | 457 | 1694 | 27.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Image Classification (HP) | 634 | 2878 | 22.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Image Classification (Q) | 377 | 2787 | 13.5% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Image Segmentation (SP) | 904 | 3152 | 28.7% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Image Segmentation (HP) | 1053 | 5906 | 17.8% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Image Segmentation (Q) | 1159 | 4081 | 28.4% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Pose Estimation (SP) | 712 | 11562 | 6.2% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Pose Estimation (HP) | 1278 | 18146 | 7.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Pose Estimation (Q) | 1289 | 16023 | 8.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Object Detection (SP) | 395 | 982 | 40.2% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Object Detection (HP) | 603 | 1266 | 47.6% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Object Detection (Q) | 685 | 1236 | 55.4% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Face Detection (SP) | 1417 | 3683 | 38.5% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Face Detection (HP) | 1387 | 6278 | 22.1% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Face Detection (Q) | 1463 | 6159 | 23.8% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Depth Estimation (SP) | 1088 | 3780 | 28.8% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Depth Estimation (HP) | 2265 | 4202 | 53.9% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Depth Estimation (Q) | 1828 | 3326 | 55.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Style Transfer (SP) | 2751 | 8252 | 33.3% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Style Transfer (HP) | 6068 | 17809 | 34.1% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Style Transfer (Q) | 6150 | 20444 | 30.1% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Image Super-Resolution (SP) | 367 | 2087 | 17.6% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Image Super-Resolution (HP) | 468 | 3388 | 13.8% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Image Super-Resolution (Q) | 440 | 2650 | 16.6% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Text Classification (SP) | 170 | 38 | 447.4% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Text Classification (HP) | 171 | 36 | 475.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Text Classification (Q) | 301 | 31 | 971.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Machine Translation (SP) | 390 | 534 | 73.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Machine Translation (HP) | 393 | 928 | 42.3% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
| Machine Translation (Q) | 341 | 383 | 89.0% |
| realme RMX3300 | |||
| samsung SM-F966U1 | |||
