iPhone 15 Pro
Geekbench AI Score
3769
Single Precision Score
25809
Half Precision Score
36426
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | iClondike |
| Upload Date | August 02 2025 07:31 AM |
| Views | 9 |
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 |
| 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% |
1678
312.0 IPS |
|
|
Image Classification (HP)
|
100% |
11023
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
17617
3.29 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1569
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
16196
262.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
21374
346.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7086
8.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
101425
118.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
205237
240.5 IPS |
|
|
Object Detection (SP)
|
100% |
1719
136.3 IPS |
|
|
Object Detection (HP)
|
100% |
14727
1.17 KIPS |
|
|
Object Detection (Q)
|
91% |
19278
1.54 KIPS |
|
|
Face Detection (SP)
|
100% |
2980
35.4 IPS |
|
|
Face Detection (HP)
|
100% |
36888
438.3 IPS |
|
|
Face Detection (Q)
|
100% |
53469
635.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6603
50.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
78565
605.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
127974
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
19647
25.3 IPS |
|
|
Style Transfer (HP)
|
100% |
206162
265.0 IPS |
|
|
Style Transfer (Q)
|
96% |
255226
329.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4541
167.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34206
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
63513
2.35 KIPS |
|
|
Text Classification (SP)
|
100% |
3241
4.33 KIPS |
|
|
Text Classification (HP)
|
100% |
3673
4.90 KIPS |
|
|
Text Classification (Q)
|
93% |
3323
4.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
3172
54.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6551
112.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7490
129.4 IPS |
