iPhone 14 Pro
Geekbench AI Score
3547
Single Precision Score
21965
Half Precision Score
25310
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 22 2024 09:25 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| Model | iPhone 14 Pro |
| Model ID | iPhone15,2 |
| Motherboard | D73AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.53 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1438
267.5 IPS |
|
|
Image Classification (HP)
|
100% |
10091
1.88 KIPS |
|
|
Image Classification (Q)
|
97% |
12854
2.40 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1450
23.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
13495
218.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
17906
290.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
6848
7.99 IPS |
|
|
Pose Estimation (HP)
|
100% |
95758
111.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
101429
118.9 IPS |
|
|
Object Detection (SP)
|
100% |
1587
125.9 IPS |
|
|
Object Detection (HP)
|
100% |
12888
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14822
1.18 KIPS |
|
|
Face Detection (SP)
|
100% |
3174
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
30737
365.2 IPS |
|
|
Face Detection (Q)
|
100% |
40267
478.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6134
47.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
75668
583.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
97167
759.7 IPS |
|
|
Style Transfer (SP)
|
100% |
18955
24.4 IPS |
|
|
Style Transfer (HP)
|
100% |
166793
214.4 IPS |
|
|
Style Transfer (Q)
|
96% |
173333
223.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4231
156.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31555
1.17 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36567
1.35 KIPS |
|
|
Text Classification (SP)
|
100% |
2613
3.49 KIPS |
|
|
Text Classification (HP)
|
100% |
2270
3.03 KIPS |
|
|
Text Classification (Q)
|
93% |
2080
2.79 KIPS |
|
|
Machine Translation (SP)
|
100% |
3419
58.9 IPS |
|
|
Machine Translation (HP)
|
100% |
5599
96.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6045
104.5 IPS |
