iPhone 15 Pro
Geekbench AI Score
4731
Single Precision Score
5625
Half Precision Score
5109
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | calvinh |
| Upload Date | October 27 2024 06:39 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| 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% |
1871
347.9 IPS |
|
|
Image Classification (HP)
|
100% |
2029
377.2 IPS |
|
|
Image Classification (Q)
|
97% |
1932
360.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2888
46.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
3761
61.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
3763
61.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
13400
15.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
14237
16.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
13479
15.8 IPS |
|
|
Object Detection (SP)
|
100% |
2427
192.5 IPS |
|
|
Object Detection (HP)
|
100% |
2730
216.6 IPS |
|
|
Object Detection (Q)
|
91% |
2337
186.8 IPS |
|
|
Face Detection (SP)
|
100% |
6153
73.1 IPS |
|
|
Face Detection (HP)
|
100% |
8713
103.5 IPS |
|
|
Face Detection (Q)
|
100% |
6181
73.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
11048
85.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
11903
91.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
10636
83.1 IPS |
|
|
Style Transfer (SP)
|
100% |
27778
35.7 IPS |
|
|
Style Transfer (HP)
|
100% |
32235
41.4 IPS |
|
|
Style Transfer (Q)
|
96% |
31541
40.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5866
216.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6189
228.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4950
182.8 IPS |
|
|
Text Classification (SP)
|
100% |
3200
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
5505
7.35 KIPS |
|
|
Text Classification (Q)
|
93% |
5488
7.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
902
15.5 IPS |
|
|
Machine Translation (HP)
|
100% |
940
16.2 IPS |
|
|
Machine Translation (Q)
|
98% |
941
16.3 IPS |
