iPhone 16 Pro
Geekbench AI Score
4780
Single Precision Score
31607
Half Precision Score
44818
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | TeckFire |
| Upload Date | March 19 2025 04:54 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| Model | iPhone 16 Pro |
| Model ID | iPhone17,1 |
| Motherboard | D93AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2076
386.0 IPS |
|
|
Image Classification (HP)
|
100% |
14953
2.78 KIPS |
|
|
Image Classification (Q)
|
97% |
20390
3.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2019
32.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
18343
297.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
23919
387.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
9745
11.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
152815
178.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
292070
342.3 IPS |
|
|
Object Detection (SP)
|
100% |
2379
188.7 IPS |
|
|
Object Detection (HP)
|
100% |
16290
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22329
1.78 KIPS |
|
|
Face Detection (SP)
|
100% |
4019
47.7 IPS |
|
|
Face Detection (HP)
|
100% |
41155
489.0 IPS |
|
|
Face Detection (Q)
|
100% |
56971
676.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8444
65.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
94694
729.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
158836
1.24 KIPS |
|
|
Style Transfer (SP)
|
100% |
21686
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
245024
315.0 IPS |
|
|
Style Transfer (Q)
|
96% |
304607
393.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5975
220.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50803
1.88 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
85366
3.15 KIPS |
|
|
Text Classification (SP)
|
100% |
3388
4.52 KIPS |
|
|
Text Classification (HP)
|
100% |
3039
4.06 KIPS |
|
|
Text Classification (Q)
|
93% |
4079
5.47 KIPS |
|
|
Machine Translation (SP)
|
100% |
4309
74.2 IPS |
|
|
Machine Translation (HP)
|
100% |
9885
170.3 IPS |
|
|
Machine Translation (Q)
|
98% |
10711
185.1 IPS |
