iPhone 16 Pro
Geekbench AI Score
4561
Single Precision Score
33332
Half Precision Score
46531
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | eahyndman3 |
| Upload Date | December 12 2024 01:37 AM |
| Views | 12 |
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
377.0 IPS |
|
|
Image Classification (HP)
|
100% |
15360
2.86 KIPS |
|
|
Image Classification (Q)
|
97% |
20801
3.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1960
31.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
18242
295.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
24232
392.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
8865
10.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
152993
178.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
293032
343.5 IPS |
|
|
Object Detection (SP)
|
100% |
2183
173.2 IPS |
|
|
Object Detection (HP)
|
100% |
16316
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22891
1.83 KIPS |
|
|
Face Detection (SP)
|
100% |
3693
43.9 IPS |
|
|
Face Detection (HP)
|
100% |
41261
490.3 IPS |
|
|
Face Detection (Q)
|
100% |
58806
698.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7835
60.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
95607
736.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
162226
1.27 KIPS |
|
|
Style Transfer (SP)
|
100% |
24019
30.9 IPS |
|
|
Style Transfer (HP)
|
100% |
244446
314.2 IPS |
|
|
Style Transfer (Q)
|
96% |
305657
394.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5487
202.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52496
1.94 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84644
3.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3455
4.61 KIPS |
|
|
Text Classification (HP)
|
100% |
4724
6.31 KIPS |
|
|
Text Classification (Q)
|
93% |
5007
6.72 KIPS |
|
|
Machine Translation (SP)
|
100% |
3847
66.3 IPS |
|
|
Machine Translation (HP)
|
100% |
10121
174.3 IPS |
|
|
Machine Translation (Q)
|
98% |
11388
196.8 IPS |
