iPhone 14 Pro
Geekbench AI Score
3511
Single Precision Score
20172
Half Precision Score
22691
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | l3uzz |
| Upload Date | October 08 2024 03:23 PM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.0.1 |
| 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% |
1398
260.1 IPS |
|
|
Image Classification (HP)
|
100% |
10422
1.94 KIPS |
|
|
Image Classification (Q)
|
97% |
12523
2.34 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1451
23.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
11835
191.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
13903
225.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
6562
7.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
95805
111.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
101480
118.9 IPS |
|
|
Object Detection (SP)
|
100% |
1564
124.1 IPS |
|
|
Object Detection (HP)
|
100% |
12630
1.00 KIPS |
|
|
Object Detection (Q)
|
91% |
15131
1.21 KIPS |
|
|
Face Detection (SP)
|
100% |
3123
37.1 IPS |
|
|
Face Detection (HP)
|
100% |
31394
373.0 IPS |
|
|
Face Detection (Q)
|
100% |
40935
486.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6235
48.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
75816
584.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
97517
762.4 IPS |
|
|
Style Transfer (SP)
|
100% |
18675
24.0 IPS |
|
|
Style Transfer (HP)
|
100% |
172883
222.2 IPS |
|
|
Style Transfer (Q)
|
96% |
169108
218.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4100
151.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31770
1.17 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37112
1.37 KIPS |
|
|
Text Classification (SP)
|
100% |
2625
3.50 KIPS |
|
|
Text Classification (HP)
|
100% |
2399
3.20 KIPS |
|
|
Text Classification (Q)
|
93% |
2301
3.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
3496
60.2 IPS |
|
|
Machine Translation (HP)
|
100% |
2384
41.1 IPS |
|
|
Machine Translation (Q)
|
98% |
2349
40.6 IPS |
