iPhone XS Max
Geekbench AI Score
646
Single Precision Score
1068
Half Precision Score
965
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | flipflop |
| Upload Date | September 13 2025 04:02 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A12 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.6 |
| 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 |
| Memory Information | |
|---|---|
| Size | 3.67 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
348
64.7 IPS |
|
|
Image Classification (HP)
|
100% |
655
121.9 IPS |
|
|
Image Classification (Q)
|
96% |
535
99.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
383
6.20 IPS |
|
|
Image Segmentation (HP)
|
100% |
724
11.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
786
12.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1195
1.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1104
1.29 IPS |
|
|
Pose Estimation (Q)
|
96% |
1040
1.22 IPS |
|
|
Object Detection (SP)
|
100% |
350
27.8 IPS |
|
|
Object Detection (HP)
|
99% |
693
55.0 IPS |
|
|
Object Detection (Q)
|
92% |
572
45.7 IPS |
|
|
Face Detection (SP)
|
100% |
929
11.0 IPS |
|
|
Face Detection (HP)
|
100% |
1818
21.6 IPS |
|
|
Face Detection (Q)
|
100% |
1230
14.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
940
7.25 IPS |
|
|
Depth Estimation (HP)
|
98% |
1632
12.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
1407
11.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2293
2.95 IPS |
|
|
Style Transfer (HP)
|
100% |
3840
4.94 IPS |
|
|
Style Transfer (Q)
|
96% |
3695
4.77 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
679
25.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
842
31.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
733
27.1 IPS |
|
|
Text Classification (SP)
|
100% |
286
381.9 IPS |
|
|
Text Classification (HP)
|
100% |
565
754.4 IPS |
|
|
Text Classification (Q)
|
93% |
565
758.0 IPS |
|
|
Machine Translation (SP)
|
100% |
589
10.1 IPS |
|
|
Machine Translation (HP)
|
98% |
991
17.1 IPS |
|
|
Machine Translation (Q)
|
98% |
1060
18.3 IPS |
