iPhone XS
Geekbench ML Score
683
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 26 2024 12:09 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone XS |
| Model ID | iPhone11,2 |
| Motherboard | D321AP |
| 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 | 3.69 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
339
63.4 IPS |
|
|
Image Classification (F16)
|
100% |
524
98.0 IPS |
|
|
Image Classification (I8)
|
99% |
523
97.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
226
3.78 IPS |
|
|
Image Segmentation (F16)
|
100% |
281
4.70 IPS |
|
|
Image Segmentation (I8)
|
100% |
278
4.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
1079
1.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
1180
1.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1161
1.41 IPS |
|
|
Object Detection (F32)
|
100% |
305
22.8 IPS |
|
|
Object Detection (F16)
|
100% |
568
42.4 IPS |
|
|
Object Detection (I8)
|
97% |
305
22.8 IPS |
|
|
Face Detection (F32)
|
100% |
690
8.20 IPS |
|
|
Face Detection (F16)
|
97% |
1373
16.3 IPS |
|
|
Face Detection (I8)
|
96% |
1369
16.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
767
5.95 IPS |
|
|
Depth Estimation (F16)
|
100% |
1507
11.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
1513
11.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2260
2.97 IPS |
|
|
Style Transfer (F16)
|
100% |
3696
4.86 IPS |
|
|
Style Transfer (I8)
|
100% |
3389
4.46 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
620
22.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
786
28.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
815
29.1 IPS |
|
|
Text Classification (F32)
|
100% |
263
377.3 IPS |
|
|
Text Classification (F16)
|
100% |
516
741.0 IPS |
|
|
Text Classification (I8)
|
96% |
520
747.9 IPS |
|
|
Machine Translation (F32)
|
100% |
317
5.83 IPS |
|
|
Machine Translation (F16)
|
100% |
456
8.40 IPS |
|
|
Machine Translation (I8)
|
99% |
333
6.12 IPS |
