iPhone 14 Pro
Geekbench AI Score
3401
Single Precision Score
22305
Half Precision Score
25543
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | piotrga |
| Upload Date | September 21 2025 09:36 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
1360
252.8 IPS |
|
|
Image Classification (HP)
|
100% |
9910
1.84 KIPS |
|
|
Image Classification (Q)
|
97% |
11427
2.13 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1401
22.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
16018
259.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
18918
306.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6198
7.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
94865
110.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
102246
119.8 IPS |
|
|
Object Detection (SP)
|
100% |
1453
115.3 IPS |
|
|
Object Detection (HP)
|
100% |
11982
950.4 IPS |
|
|
Object Detection (Q)
|
91% |
14259
1.14 KIPS |
|
|
Face Detection (SP)
|
100% |
3106
36.9 IPS |
|
|
Face Detection (HP)
|
100% |
30926
367.5 IPS |
|
|
Face Detection (Q)
|
100% |
38959
462.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5918
45.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
71936
554.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
93100
727.9 IPS |
|
|
Style Transfer (SP)
|
100% |
18191
23.4 IPS |
|
|
Style Transfer (HP)
|
100% |
161334
207.4 IPS |
|
|
Style Transfer (Q)
|
96% |
169568
218.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3825
141.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32958
1.22 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36493
1.35 KIPS |
|
|
Text Classification (SP)
|
100% |
2780
3.71 KIPS |
|
|
Text Classification (HP)
|
100% |
1986
2.65 KIPS |
|
|
Text Classification (Q)
|
93% |
2020
2.71 KIPS |
|
|
Machine Translation (SP)
|
100% |
3400
58.6 IPS |
|
|
Machine Translation (HP)
|
100% |
7193
123.9 IPS |
|
|
Machine Translation (Q)
|
98% |
8275
143.0 IPS |
