iPhone 15 Pro
Geekbench AI Score
2667
Single Precision Score
13848
Half Precision Score
16002
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | danindub |
| Upload Date | August 17 2024 08:47 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1403
261.0 IPS |
|
|
Image Classification (HP)
|
100% |
6233
1.16 KIPS |
|
|
Image Classification (Q)
|
99% |
6872
1.28 KIPS |
|
|
Image Segmentation (SP)
|
100% |
792
12.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
5251
85.1 IPS |
|
|
Image Segmentation (Q)
|
100% |
5430
88.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7307
8.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
87648
102.3 IPS |
|
|
Pose Estimation (Q)
|
94% |
129327
151.7 IPS |
|
|
Object Detection (SP)
|
100% |
1455
115.4 IPS |
|
|
Object Detection (HP)
|
100% |
8211
651.3 IPS |
|
|
Object Detection (Q)
|
93% |
9156
730.6 IPS |
|
|
Face Detection (SP)
|
100% |
2227
26.5 IPS |
|
|
Face Detection (HP)
|
100% |
11261
133.8 IPS |
|
|
Face Detection (Q)
|
100% |
13489
160.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
4570
35.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
42684
328.9 IPS |
|
|
Depth Estimation (Q)
|
97% |
47792
369.5 IPS |
|
|
Style Transfer (SP)
|
100% |
12086
15.5 IPS |
|
|
Style Transfer (HP)
|
100% |
128107
164.7 IPS |
|
|
Style Transfer (Q)
|
100% |
128809
165.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3900
144.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18636
688.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
27828
1.03 KIPS |
|
|
Text Classification (SP)
|
100% |
1739
2.32 KIPS |
|
|
Text Classification (HP)
|
71% |
3868
5.56 KIPS |
|
|
Text Classification (Q)
|
69% |
4341
6.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
1849
31.8 IPS |
|
|
Machine Translation (HP)
|
100% |
2481
42.7 IPS |
|
|
Machine Translation (Q)
|
98% |
2485
43.0 IPS |
