iPhone 14 Pro
Geekbench AI Score
3558
Single Precision Score
23665
Half Precision Score
26951
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | winzee |
| Upload Date | May 08 2025 04:55 PM |
| Views | 10 |
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% |
1431
266.1 IPS |
|
|
Image Classification (HP)
|
100% |
10519
1.96 KIPS |
|
|
Image Classification (Q)
|
97% |
12884
2.40 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1419
23.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
15787
255.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
19194
311.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7088
8.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
99966
116.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
105097
123.2 IPS |
|
|
Object Detection (SP)
|
100% |
1580
125.3 IPS |
|
|
Object Detection (HP)
|
100% |
12898
1.02 KIPS |
|
|
Object Detection (Q)
|
91% |
14610
1.17 KIPS |
|
|
Face Detection (SP)
|
100% |
3116
37.0 IPS |
|
|
Face Detection (HP)
|
100% |
31394
373.0 IPS |
|
|
Face Detection (Q)
|
100% |
40325
479.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6117
47.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
76268
587.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
94753
740.8 IPS |
|
|
Style Transfer (SP)
|
100% |
19166
24.6 IPS |
|
|
Style Transfer (HP)
|
100% |
177537
228.2 IPS |
|
|
Style Transfer (Q)
|
96% |
184510
238.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4160
153.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32920
1.22 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
38471
1.42 KIPS |
|
|
Text Classification (SP)
|
100% |
2683
3.58 KIPS |
|
|
Text Classification (HP)
|
100% |
2439
3.26 KIPS |
|
|
Text Classification (Q)
|
93% |
2354
3.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
3509
60.4 IPS |
|
|
Machine Translation (HP)
|
100% |
7539
129.9 IPS |
|
|
Machine Translation (Q)
|
98% |
8343
144.2 IPS |
