iPhone XS Max
Geekbench ML Score
763
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 06 2024 07:18 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone XS Max |
| Model ID | iPhone11,6 |
| Motherboard | D331pAP |
| CPU Information | |
|---|---|
| Name | Apple A12 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.49 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 48.0 KB x 1 |
| L1 Data Cache | 32.0 KB x 1 |
| L2 Cache | 2.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.67 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
370
69.3 IPS |
|
|
Image Classification (F16)
|
100% |
575
107.6 IPS |
|
|
Image Classification (I8)
|
99% |
575
107.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
247
4.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
298
4.98 IPS |
|
|
Image Segmentation (I8)
|
100% |
303
5.06 IPS |
|
|
Pose Estimation (F32)
|
100% |
1199
1.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
1172
1.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
1161
1.41 IPS |
|
|
Object Detection (F32)
|
100% |
361
26.9 IPS |
|
|
Object Detection (F16)
|
100% |
633
47.2 IPS |
|
|
Object Detection (I8)
|
97% |
364
27.2 IPS |
|
|
Face Detection (F32)
|
100% |
780
9.27 IPS |
|
|
Face Detection (F16)
|
97% |
1498
17.8 IPS |
|
|
Face Detection (I8)
|
96% |
1492
17.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
898
6.97 IPS |
|
|
Depth Estimation (F16)
|
100% |
1649
12.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
1663
12.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2570
3.38 IPS |
|
|
Style Transfer (F16)
|
100% |
4454
5.86 IPS |
|
|
Style Transfer (I8)
|
100% |
4500
5.92 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
760
27.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
954
34.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
957
34.2 IPS |
|
|
Text Classification (F32)
|
100% |
268
385.2 IPS |
|
|
Text Classification (F16)
|
100% |
520
748.0 IPS |
|
|
Text Classification (I8)
|
96% |
522
750.9 IPS |
|
|
Machine Translation (F32)
|
100% |
381
7.01 IPS |
|
|
Machine Translation (F16)
|
100% |
515
9.48 IPS |
|
|
Machine Translation (I8)
|
99% |
376
6.91 IPS |
