iPhone 16 Pro
Geekbench AI Score
4605
Single Precision Score
7793
Half Precision Score
6217
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Pom2Ter |
| Upload Date | March 03 2025 09:56 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2077
386.3 IPS |
|
|
Image Classification (HP)
|
100% |
3435
638.8 IPS |
|
|
Image Classification (Q)
|
96% |
2286
426.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2005
32.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2870
46.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
3354
54.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
9141
10.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
18177
21.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
15252
17.9 IPS |
|
|
Object Detection (SP)
|
100% |
2320
184.0 IPS |
|
|
Object Detection (HP)
|
97% |
3794
302.0 IPS |
|
|
Object Detection (Q)
|
94% |
2657
211.8 IPS |
|
|
Face Detection (SP)
|
100% |
3924
46.6 IPS |
|
|
Face Detection (HP)
|
100% |
7432
88.3 IPS |
|
|
Face Detection (Q)
|
100% |
4136
49.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
8149
62.8 IPS |
|
|
Depth Estimation (HP)
|
97% |
14368
111.1 IPS |
|
|
Depth Estimation (Q)
|
86% |
9961
77.7 IPS |
|
|
Style Transfer (SP)
|
100% |
19871
25.5 IPS |
|
|
Style Transfer (HP)
|
100% |
37804
48.6 IPS |
|
|
Style Transfer (Q)
|
96% |
30671
39.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5374
198.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7308
269.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5186
191.5 IPS |
|
|
Text Classification (SP)
|
100% |
3313
4.42 KIPS |
|
|
Text Classification (HP)
|
100% |
5703
7.61 KIPS |
|
|
Text Classification (Q)
|
93% |
5835
7.83 KIPS |
|
|
Machine Translation (SP)
|
100% |
4297
74.0 IPS |
|
|
Machine Translation (HP)
|
98% |
7228
124.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7269
125.6 IPS |
