iPhone 13 Pro
Geekbench AI Score
3248
Single Precision Score
15029
Half Precision Score
16543
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | Jfreshh330 |
| Upload Date | August 29 2024 02:39 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone 13 Pro |
| Model ID | iPhone14,2 |
| Motherboard | D63AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.54 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1355
251.9 IPS |
|
|
Image Classification (HP)
|
100% |
8346
1.55 KIPS |
|
|
Image Classification (Q)
|
99% |
9554
1.78 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1300
21.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
6499
105.3 IPS |
|
|
Image Segmentation (Q)
|
100% |
6776
109.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6259
7.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
84448
98.5 IPS |
|
|
Pose Estimation (Q)
|
94% |
89909
105.5 IPS |
|
|
Object Detection (SP)
|
100% |
1426
113.1 IPS |
|
|
Object Detection (HP)
|
99% |
10260
816.1 IPS |
|
|
Object Detection (Q)
|
91% |
11247
898.7 IPS |
|
|
Face Detection (SP)
|
100% |
2707
32.2 IPS |
|
|
Face Detection (HP)
|
100% |
17612
209.3 IPS |
|
|
Face Detection (Q)
|
100% |
28272
335.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5467
42.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
47560
366.4 IPS |
|
|
Depth Estimation (Q)
|
97% |
52435
405.4 IPS |
|
|
Style Transfer (SP)
|
100% |
17258
22.2 IPS |
|
|
Style Transfer (HP)
|
100% |
108981
140.1 IPS |
|
|
Style Transfer (Q)
|
100% |
108398
139.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3958
146.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26219
968.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
27765
1.03 KIPS |
|
|
Text Classification (SP)
|
100% |
2409
3.22 KIPS |
|
|
Text Classification (HP)
|
100% |
2324
3.10 KIPS |
|
|
Text Classification (Q)
|
93% |
2386
3.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3419
58.9 IPS |
|
|
Machine Translation (HP)
|
100% |
2249
38.7 IPS |
|
|
Machine Translation (Q)
|
98% |
2204
38.1 IPS |
