iPhone 14 Pro
Geekbench AI Score
3401
Single Precision Score
23464
Half Precision Score
26638
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | bgh0809 |
| Upload Date | November 19 2025 09:58 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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% |
1304
242.5 IPS |
|
|
Image Classification (HP)
|
100% |
9621
1.79 KIPS |
|
|
Image Classification (Q)
|
97% |
12220
2.28 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1384
22.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
15139
245.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
18943
307.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6328
7.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
100551
117.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
102867
120.6 IPS |
|
|
Object Detection (SP)
|
100% |
1459
115.7 IPS |
|
|
Object Detection (HP)
|
100% |
12665
1.00 KIPS |
|
|
Object Detection (Q)
|
91% |
14670
1.17 KIPS |
|
|
Face Detection (SP)
|
100% |
3086
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
31157
370.2 IPS |
|
|
Face Detection (Q)
|
100% |
40054
475.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5863
45.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
72406
557.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
92032
719.6 IPS |
|
|
Style Transfer (SP)
|
100% |
18464
23.7 IPS |
|
|
Style Transfer (HP)
|
100% |
173340
222.8 IPS |
|
|
Style Transfer (Q)
|
96% |
172813
223.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3969
146.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32375
1.20 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
35343
1.31 KIPS |
|
|
Text Classification (SP)
|
100% |
2774
3.70 KIPS |
|
|
Text Classification (HP)
|
100% |
2942
3.93 KIPS |
|
|
Text Classification (Q)
|
93% |
2775
3.72 KIPS |
|
|
Machine Translation (SP)
|
100% |
3382
58.3 IPS |
|
|
Machine Translation (HP)
|
100% |
7324
126.2 IPS |
|
|
Machine Translation (Q)
|
98% |
8244
142.5 IPS |
