iPhone 14 Pro
Geekbench AI Score
3481
Single Precision Score
22866
Half Precision Score
26843
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | y561994 |
| Upload Date | March 10 2025 03:09 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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% |
1403
260.9 IPS |
|
|
Image Classification (HP)
|
100% |
9942
1.85 KIPS |
|
|
Image Classification (Q)
|
97% |
12151
2.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1426
23.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
14505
235.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
19108
309.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6465
7.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
96381
112.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
104389
122.4 IPS |
|
|
Object Detection (SP)
|
100% |
1570
124.6 IPS |
|
|
Object Detection (HP)
|
100% |
13110
1.04 KIPS |
|
|
Object Detection (Q)
|
91% |
14663
1.17 KIPS |
|
|
Face Detection (SP)
|
100% |
3079
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
31965
379.8 IPS |
|
|
Face Detection (Q)
|
100% |
41135
488.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6006
46.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
75116
578.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
97441
761.8 IPS |
|
|
Style Transfer (SP)
|
100% |
18155
23.3 IPS |
|
|
Style Transfer (HP)
|
100% |
166534
214.1 IPS |
|
|
Style Transfer (Q)
|
96% |
173456
223.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3981
147.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33290
1.23 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37210
1.37 KIPS |
|
|
Text Classification (SP)
|
100% |
2711
3.62 KIPS |
|
|
Text Classification (HP)
|
100% |
2108
2.81 KIPS |
|
|
Text Classification (Q)
|
93% |
2530
3.40 KIPS |
|
|
Machine Translation (SP)
|
100% |
3557
61.3 IPS |
|
|
Machine Translation (HP)
|
100% |
7645
131.7 IPS |
|
|
Machine Translation (Q)
|
98% |
8351
144.3 IPS |
