iPhone 15 Pro
Geekbench AI Score
3943
Single Precision Score
6988
Half Precision Score
5707
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 24 2025 12:45 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4.1 |
| 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 | 7.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1707
317.4 IPS |
|
|
Image Classification (HP)
|
100% |
2983
554.7 IPS |
|
|
Image Classification (Q)
|
96% |
2047
382.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1606
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2363
38.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
3061
49.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
8063
9.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
16625
19.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
14341
16.8 IPS |
|
|
Object Detection (SP)
|
100% |
1781
141.2 IPS |
|
|
Object Detection (HP)
|
97% |
3352
266.8 IPS |
|
|
Object Detection (Q)
|
94% |
2378
189.6 IPS |
|
|
Face Detection (SP)
|
100% |
3202
38.1 IPS |
|
|
Face Detection (HP)
|
100% |
6843
81.3 IPS |
|
|
Face Detection (Q)
|
100% |
3828
45.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6819
52.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
12892
99.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
9034
70.6 IPS |
|
|
Style Transfer (SP)
|
100% |
21229
27.3 IPS |
|
|
Style Transfer (HP)
|
100% |
34114
43.9 IPS |
|
|
Style Transfer (Q)
|
96% |
27868
36.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4797
177.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5754
212.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4429
163.5 IPS |
|
|
Text Classification (SP)
|
100% |
3236
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
5700
7.61 KIPS |
|
|
Text Classification (Q)
|
93% |
5647
7.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
3212
55.3 IPS |
|
|
Machine Translation (HP)
|
98% |
7166
123.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7123
123.1 IPS |
