iPhone 15 Pro
Geekbench AI Score
4039
Single Precision Score
25128
Half Precision Score
33007
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | calvinh |
| Upload Date | January 22 2025 08:19 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3 |
| 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% |
1698
315.8 IPS |
|
|
Image Classification (HP)
|
100% |
11179
2.08 KIPS |
|
|
Image Classification (Q)
|
97% |
14920
2.78 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1642
26.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
15833
256.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
20870
338.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8481
9.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
106736
124.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
204282
239.4 IPS |
|
|
Object Detection (SP)
|
100% |
1837
145.7 IPS |
|
|
Object Detection (HP)
|
100% |
13857
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
18624
1.49 KIPS |
|
|
Face Detection (SP)
|
100% |
3249
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
34138
405.6 IPS |
|
|
Face Detection (Q)
|
100% |
50422
599.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7191
55.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78374
603.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
128951
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21957
28.2 IPS |
|
|
Style Transfer (HP)
|
100% |
206183
265.1 IPS |
|
|
Style Transfer (Q)
|
96% |
250628
323.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5127
189.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35018
1.29 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55914
2.06 KIPS |
|
|
Text Classification (SP)
|
100% |
3201
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3211
4.29 KIPS |
|
|
Text Classification (Q)
|
93% |
1893
2.54 KIPS |
|
|
Machine Translation (SP)
|
100% |
3162
54.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6182
106.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7512
129.8 IPS |
