iPhone 13 Pro
Geekbench AI Score
3271
Single Precision Score
20468
Half Precision Score
22712
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | April 02 2026 06:57 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.7.7 |
| 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% |
1322
245.8 IPS |
|
|
Image Classification (HP)
|
100% |
8186
1.52 KIPS |
|
|
Image Classification (Q)
|
96% |
9526
1.78 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1313
21.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12965
210.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
14589
236.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6369
7.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
94705
110.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
93782
109.9 IPS |
|
|
Object Detection (SP)
|
100% |
1459
115.7 IPS |
|
|
Object Detection (HP)
|
99% |
10958
871.7 IPS |
|
|
Object Detection (Q)
|
91% |
11186
893.8 IPS |
|
|
Face Detection (SP)
|
100% |
2696
32.0 IPS |
|
|
Face Detection (HP)
|
100% |
29293
348.1 IPS |
|
|
Face Detection (Q)
|
100% |
36791
437.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5339
41.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
56630
436.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
74296
580.6 IPS |
|
|
Style Transfer (SP)
|
100% |
17246
22.2 IPS |
|
|
Style Transfer (HP)
|
100% |
162883
209.4 IPS |
|
|
Style Transfer (Q)
|
96% |
169623
218.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3895
143.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
28339
1.05 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31355
1.16 KIPS |
|
|
Text Classification (SP)
|
100% |
2478
3.31 KIPS |
|
|
Text Classification (HP)
|
100% |
2468
3.29 KIPS |
|
|
Text Classification (Q)
|
93% |
2452
3.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
3634
62.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6203
106.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7029
121.5 IPS |
