iPhone 15 Pro Max
Geekbench AI Score
3944
Single Precision Score
25175
Half Precision Score
35813
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | June 12 2025 12:40 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1693
314.9 IPS |
|
|
Image Classification (HP)
|
100% |
10721
1.99 KIPS |
|
|
Image Classification (Q)
|
97% |
15949
2.98 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1599
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
16342
264.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
21636
350.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7900
9.22 IPS |
|
|
Pose Estimation (HP)
|
100% |
105890
123.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
207292
243.0 IPS |
|
|
Object Detection (SP)
|
100% |
1788
141.8 IPS |
|
|
Object Detection (HP)
|
100% |
13790
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18872
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
3166
37.6 IPS |
|
|
Face Detection (HP)
|
100% |
33674
400.1 IPS |
|
|
Face Detection (Q)
|
100% |
51468
611.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7029
54.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
78759
606.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
129677
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21187
27.2 IPS |
|
|
Style Transfer (HP)
|
100% |
208960
268.6 IPS |
|
|
Style Transfer (Q)
|
96% |
249894
322.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4893
180.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34167
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58484
2.16 KIPS |
|
|
Text Classification (SP)
|
100% |
3249
4.34 KIPS |
|
|
Text Classification (HP)
|
100% |
3230
4.31 KIPS |
|
|
Text Classification (Q)
|
93% |
3425
4.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
3181
54.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6536
112.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7697
133.0 IPS |
