iPhone 14 Pro
Geekbench AI Score
2398
Single Precision Score
12781
Half Precision Score
13940
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | Lucky_n00b |
| Upload Date | August 16 2024 10:05 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 5.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1234
229.5 IPS |
|
|
Image Classification (HP)
|
100% |
5785
1.08 KIPS |
|
|
Image Classification (Q)
|
99% |
6183
1.15 KIPS |
|
|
Image Segmentation (SP)
|
100% |
750
12.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
5124
83.1 IPS |
|
|
Image Segmentation (Q)
|
100% |
5134
83.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6519
7.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
77693
90.7 IPS |
|
|
Pose Estimation (Q)
|
94% |
85232
100.0 IPS |
|
|
Object Detection (SP)
|
100% |
1323
105.0 IPS |
|
|
Object Detection (HP)
|
100% |
7691
610.0 IPS |
|
|
Object Detection (Q)
|
93% |
8302
662.4 IPS |
|
|
Face Detection (SP)
|
100% |
2190
26.0 IPS |
|
|
Face Detection (HP)
|
100% |
10914
129.7 IPS |
|
|
Face Detection (Q)
|
100% |
13171
156.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
4160
32.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
39423
303.7 IPS |
|
|
Depth Estimation (Q)
|
97% |
47882
370.2 IPS |
|
|
Style Transfer (SP)
|
100% |
11379
14.6 IPS |
|
|
Style Transfer (HP)
|
100% |
122087
156.9 IPS |
|
|
Style Transfer (Q)
|
100% |
122165
157.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3327
122.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16304
602.0 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
21416
793.4 IPS |
|
|
Text Classification (SP)
|
100% |
1375
1.84 KIPS |
|
|
Text Classification (HP)
|
100% |
3161
4.22 KIPS |
|
|
Text Classification (Q)
|
93% |
3190
4.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
1666
28.7 IPS |
|
|
Machine Translation (HP)
|
100% |
2427
41.8 IPS |
|
|
Machine Translation (Q)
|
98% |
2345
40.5 IPS |
