iPhone 15 Pro
Geekbench AI Score
3955
Single Precision Score
6862
Half Precision Score
5582
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | September 17 2024 10:55 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 | 7.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1722
320.2 IPS |
|
|
Image Classification (HP)
|
100% |
2947
548.1 IPS |
|
|
Image Classification (Q)
|
96% |
2024
377.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1615
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2399
38.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
3084
50.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7983
9.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
16207
18.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
14203
16.6 IPS |
|
|
Object Detection (SP)
|
100% |
1800
142.8 IPS |
|
|
Object Detection (HP)
|
97% |
3343
266.1 IPS |
|
|
Object Detection (Q)
|
94% |
2342
186.7 IPS |
|
|
Face Detection (SP)
|
100% |
3242
38.5 IPS |
|
|
Face Detection (HP)
|
100% |
6775
80.5 IPS |
|
|
Face Detection (Q)
|
100% |
3856
45.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7058
54.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
13512
104.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
9290
72.6 IPS |
|
|
Style Transfer (SP)
|
100% |
21073
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
32374
41.6 IPS |
|
|
Style Transfer (Q)
|
96% |
27217
35.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4814
177.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5913
218.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4350
160.6 IPS |
|
|
Text Classification (SP)
|
100% |
3218
4.30 KIPS |
|
|
Text Classification (HP)
|
100% |
5644
7.53 KIPS |
|
|
Text Classification (Q)
|
93% |
5479
7.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
3140
54.1 IPS |
|
|
Machine Translation (HP)
|
98% |
6111
105.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6089
105.2 IPS |
