iPhone XS Max
Geekbench ML Score
495
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 08 2024 03:47 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.6.1 |
| 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% |
273
51.0 IPS |
|
|
Image Classification (F16)
|
100% |
245
45.9 IPS |
|
|
Image Classification (I8)
|
99% |
246
46.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
245
4.09 IPS |
|
|
Image Segmentation (F16)
|
100% |
240
4.01 IPS |
|
|
Image Segmentation (I8)
|
100% |
234
3.91 IPS |
|
|
Pose Estimation (F32)
|
100% |
932
1.13 IPS |
|
|
Pose Estimation (F16)
|
100% |
1005
1.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
904
1.09 IPS |
|
|
Object Detection (F32)
|
100% |
307
22.9 IPS |
|
|
Object Detection (F16)
|
100% |
281
21.0 IPS |
|
|
Object Detection (I8)
|
97% |
302
22.5 IPS |
|
|
Face Detection (F32)
|
100% |
625
7.43 IPS |
|
|
Face Detection (F16)
|
100% |
618
7.34 IPS |
|
|
Face Detection (I8)
|
99% |
621
7.38 IPS |
|
|
Depth Estimation (F32)
|
100% |
762
5.91 IPS |
|
|
Depth Estimation (F16)
|
100% |
691
5.36 IPS |
|
|
Depth Estimation (I8)
|
99% |
685
5.31 IPS |
|
|
Style Transfer (F32)
|
100% |
1833
2.41 IPS |
|
|
Style Transfer (F16)
|
100% |
1812
2.38 IPS |
|
|
Style Transfer (I8)
|
100% |
1659
2.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
646
23.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
645
23.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
654
23.3 IPS |
|
|
Text Classification (F32)
|
100% |
269
386.7 IPS |
|
|
Text Classification (F16)
|
100% |
281
403.8 IPS |
|
|
Text Classification (I8)
|
96% |
280
402.8 IPS |
|
|
Machine Translation (F32)
|
100% |
425
7.83 IPS |
|
|
Machine Translation (F16)
|
100% |
321
5.91 IPS |
|
|
Machine Translation (I8)
|
99% |
389
7.16 IPS |
