iPhone 15 Pro
Geekbench AI Score
3857
Single Precision Score
24931
Half Precision Score
33628
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | calvinh |
| Upload Date | October 27 2024 06:42 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| Model | iPhone 15 Pro |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| 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 | 7.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1652
307.2 IPS |
|
|
Image Classification (HP)
|
100% |
11622
2.16 KIPS |
|
|
Image Classification (Q)
|
97% |
15298
2.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1591
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
15716
254.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
20924
339.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7604
8.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
102349
119.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
203166
238.1 IPS |
|
|
Object Detection (SP)
|
100% |
1758
139.4 IPS |
|
|
Object Detection (HP)
|
100% |
13707
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19135
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3152
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
34283
407.4 IPS |
|
|
Face Detection (Q)
|
100% |
50373
598.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6793
52.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78725
606.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
127086
993.6 IPS |
|
|
Style Transfer (SP)
|
100% |
20195
26.0 IPS |
|
|
Style Transfer (HP)
|
100% |
200769
258.1 IPS |
|
|
Style Transfer (Q)
|
96% |
248632
320.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4776
176.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34092
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
60295
2.23 KIPS |
|
|
Text Classification (SP)
|
100% |
3199
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3194
4.26 KIPS |
|
|
Text Classification (Q)
|
93% |
2067
2.77 KIPS |
|
|
Machine Translation (SP)
|
100% |
3144
54.2 IPS |
|
|
Machine Translation (HP)
|
100% |
6136
105.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7493
129.5 IPS |
