iPhone 16 Pro Max vs LENOVO 83E2
| iPhone 16 Pro Max | LENOVO 83E2 | Difference | |
|---|---|---|---|
| Single Precision | 4700 | 2936 | 160.1% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Half Precision | 32957 | 1158 | 2846.0% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Quantized | 45563 | 2344 | 1943.8% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Geekbench AI 1.2.0 | Geekbench AI 1.1.0 | ||
System Information
| iPhone 16 Pro Max | LENOVO 83E2 | |
|---|---|---|
| AI Framework | Core ML | ONNX |
| AI Backend | Neural Engine | DirectML |
| AI Device | Apple A18 Pro | Intel(R) Arc(TM) Graphics |
| Operating System | iOS 18.4 | Microsoft Windows 11 Pro (64-bit) |
| Model | iPhone 16 Pro Max | LENOVO 83E2 |
| Processor |
Apple A18 Pro @ 4.04 GHz
1 Processor, 6 Cores |
Intel Core Ultra 7 155H @ 1.40 GHz
1 Processor, 16 Cores, 22 Threads |
| Processor ID | ARM | GenuineIntel Family 6 Model 170 Stepping 4 |
| Processor Codename | ||
| Processor Package | ||
| Motherboard | D94AP | LENOVO LNVNB161216 |
| Northbridge | ||
| Southbridge | ||
| BIOS | LENOVO N9CN28WW | |
| Memory | 7.45 GB | 32.00 GB |
AI Performance
| iPhone 16 Pro Max | LENOVO 83E2 | Difference | |
|---|---|---|---|
| Image Classification (SP) | 2070 | 1086 | 190.6% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Image Classification (HP) | 15151 | 0 | |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Image Classification (Q) | 19006 | 1018 | 1867.0% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Image Segmentation (SP) | 2002 | 1561 | 128.3% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Image Segmentation (HP) | 18389 | 6790 | 270.8% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Image Segmentation (Q) | 24138 | 1374 | 1756.8% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Pose Estimation (SP) | 9702 | 14802 | 65.5% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Pose Estimation (HP) | 153520 | 19978 | 768.4% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Pose Estimation (Q) | 292587 | 13025 | 2246.3% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Object Detection (SP) | 2369 | 1268 | 186.8% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Object Detection (HP) | 16140 | 0 | |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Object Detection (Q) | 22442 | 1050 | 2137.3% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Face Detection (SP) | 3954 | 1326 | 298.2% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Face Detection (HP) | 41210 | 7804 | 528.1% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Face Detection (Q) | 57137 | 1214 | 4706.5% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Depth Estimation (SP) | 8356 | 7449 | 112.2% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Depth Estimation (HP) | 96223 | 17956 | 535.9% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Depth Estimation (Q) | 160074 | 6025 | 2656.8% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Style Transfer (SP) | 21059 | 43479 | 48.4% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Style Transfer (HP) | 246053 | 61966 | 397.1% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Style Transfer (Q) | 300790 | 33677 | 893.2% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Image Super-Resolution (SP) | 5630 | 6341 | 88.8% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Image Super-Resolution (HP) | 50756 | 6755 | 751.4% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Image Super-Resolution (Q) | 83925 | 4521 | 1856.3% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Text Classification (SP) | 3382 | 469 | 721.1% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Text Classification (HP) | 4373 | 464 | 942.5% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Text Classification (Q) | 5034 | 385 | 1307.5% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Machine Translation (SP) | 4169 | 1173 | 355.4% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Machine Translation (HP) | 10113 | 1176 | 859.9% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
| Machine Translation (Q) | 11014 | 613 | 1796.7% |
| iPhone 16 Pro Max | |||
| LENOVO 83E2 | |||
