iPhone XS Max
Geekbench ML Score
733
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 24 2024 05:45 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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% |
360
67.4 IPS |
|
|
Image Classification (F16)
|
100% |
563
105.3 IPS |
|
|
Image Classification (I8)
|
99% |
563
105.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
245
4.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
292
4.88 IPS |
|
|
Image Segmentation (I8)
|
100% |
292
4.88 IPS |
|
|
Pose Estimation (F32)
|
100% |
1113
1.35 IPS |
|
|
Pose Estimation (F16)
|
100% |
1108
1.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
1117
1.35 IPS |
|
|
Object Detection (F32)
|
100% |
369
27.5 IPS |
|
|
Object Detection (F16)
|
100% |
624
46.6 IPS |
|
|
Object Detection (I8)
|
97% |
365
27.3 IPS |
|
|
Face Detection (F32)
|
100% |
772
9.17 IPS |
|
|
Face Detection (F16)
|
97% |
1407
16.7 IPS |
|
|
Face Detection (I8)
|
96% |
1441
17.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
789
6.12 IPS |
|
|
Depth Estimation (F16)
|
100% |
1660
12.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
1653
12.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2276
2.99 IPS |
|
|
Style Transfer (F16)
|
100% |
4042
5.32 IPS |
|
|
Style Transfer (I8)
|
100% |
4301
5.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
719
25.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
967
34.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
969
34.6 IPS |
|
|
Text Classification (F32)
|
100% |
267
383.1 IPS |
|
|
Text Classification (F16)
|
100% |
519
745.6 IPS |
|
|
Text Classification (I8)
|
96% |
519
746.3 IPS |
|
|
Machine Translation (F32)
|
100% |
350
6.44 IPS |
|
|
Machine Translation (F16)
|
100% |
467
8.59 IPS |
|
|
Machine Translation (I8)
|
99% |
319
5.88 IPS |
