iPhone 16 Pro
Geekbench AI Score
4527
Single Precision Score
32907
Half Precision Score
46093
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | MarkJWilcox |
| Upload Date | December 14 2024 09:14 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
2027
376.9 IPS |
|
|
Image Classification (HP)
|
100% |
15347
2.85 KIPS |
|
|
Image Classification (Q)
|
97% |
20444
3.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1926
31.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
18243
295.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
24010
389.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8470
9.88 IPS |
|
|
Pose Estimation (HP)
|
100% |
153722
179.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
293394
343.9 IPS |
|
|
Object Detection (SP)
|
100% |
2158
171.1 IPS |
|
|
Object Detection (HP)
|
100% |
16215
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22921
1.83 KIPS |
|
|
Face Detection (SP)
|
100% |
3619
43.0 IPS |
|
|
Face Detection (HP)
|
100% |
41310
490.8 IPS |
|
|
Face Detection (Q)
|
100% |
58347
693.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7722
59.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
94921
731.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
160176
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
23844
30.7 IPS |
|
|
Style Transfer (HP)
|
100% |
244688
314.6 IPS |
|
|
Style Transfer (Q)
|
96% |
300673
388.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5646
208.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50595
1.87 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83541
3.08 KIPS |
|
|
Text Classification (SP)
|
100% |
3498
4.67 KIPS |
|
|
Text Classification (HP)
|
100% |
4665
6.23 KIPS |
|
|
Text Classification (Q)
|
93% |
4909
6.59 KIPS |
|
|
Machine Translation (SP)
|
100% |
3856
66.4 IPS |
|
|
Machine Translation (HP)
|
100% |
9422
162.3 IPS |
|
|
Machine Translation (Q)
|
98% |
11380
196.7 IPS |
