iPhone 13 Pro
Geekbench AI Score
3306
Single Precision Score
20376
Half Precision Score
22925
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | February 13 2026 05:37 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.6.2 |
| 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% |
1343
249.7 IPS |
|
|
Image Classification (HP)
|
100% |
8391
1.56 KIPS |
|
|
Image Classification (Q)
|
96% |
10891
2.03 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1330
21.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
13244
214.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
12999
210.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6519
7.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
86728
101.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
95582
112.0 IPS |
|
|
Object Detection (SP)
|
100% |
1476
117.1 IPS |
|
|
Object Detection (HP)
|
99% |
11264
896.1 IPS |
|
|
Object Detection (Q)
|
91% |
11164
892.0 IPS |
|
|
Face Detection (SP)
|
100% |
2723
32.4 IPS |
|
|
Face Detection (HP)
|
100% |
29408
349.4 IPS |
|
|
Face Detection (Q)
|
100% |
36960
439.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5333
41.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
57844
445.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
73907
577.6 IPS |
|
|
Style Transfer (SP)
|
100% |
17735
22.8 IPS |
|
|
Style Transfer (HP)
|
100% |
160771
206.7 IPS |
|
|
Style Transfer (Q)
|
96% |
165756
213.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3886
143.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26740
987.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
31182
1.15 KIPS |
|
|
Text Classification (SP)
|
100% |
2475
3.30 KIPS |
|
|
Text Classification (HP)
|
100% |
2439
3.26 KIPS |
|
|
Text Classification (Q)
|
93% |
2558
3.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
3674
63.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6372
109.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7350
127.0 IPS |
