iPhone 14 Pro
Geekbench AI Score
3552
Single Precision Score
22813
Half Precision Score
26897
Quantized Score
Geekbench AI 1.4.0-Beta1 Corporate for iOS AArch64
Result Information
| Upload Date | June 06 2025 07:56 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| 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% |
1439
267.5 IPS |
|
|
Image Classification (HP)
|
100% |
10361
1.93 KIPS |
|
|
Image Classification (Q)
|
97% |
12550
2.34 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1418
23.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
13586
220.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
19221
311.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6967
8.13 IPS |
|
|
Pose Estimation (HP)
|
100% |
97898
114.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
105320
123.4 IPS |
|
|
Object Detection (SP)
|
100% |
1579
125.3 IPS |
|
|
Object Detection (HP)
|
100% |
13008
1.03 KIPS |
|
|
Object Detection (Q)
|
91% |
14897
1.19 KIPS |
|
|
Face Detection (SP)
|
100% |
3051
36.3 IPS |
|
|
Face Detection (HP)
|
100% |
30932
367.5 IPS |
|
|
Face Detection (Q)
|
100% |
40227
478.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6174
47.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
75244
579.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
95631
747.7 IPS |
|
|
Style Transfer (SP)
|
100% |
19117
24.6 IPS |
|
|
Style Transfer (HP)
|
100% |
168360
216.4 IPS |
|
|
Style Transfer (Q)
|
96% |
170741
220.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4224
156.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33736
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37757
1.39 KIPS |
|
|
Text Classification (SP)
|
100% |
2716
3.63 KIPS |
|
|
Text Classification (HP)
|
100% |
2137
2.85 KIPS |
|
|
Text Classification (Q)
|
93% |
2506
3.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
3450
59.4 IPS |
|
|
Machine Translation (HP)
|
100% |
7540
129.9 IPS |
|
|
Machine Translation (Q)
|
98% |
8426
145.6 IPS |
