iPhone 13 Pro
Geekbench AI Score
3152
Single Precision Score
18086
Half Precision Score
20143
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | October 21 2025 07:58 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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 | 5.53 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1253
233.0 IPS |
|
|
Image Classification (HP)
|
100% |
7582
1.41 KIPS |
|
|
Image Classification (Q)
|
96% |
8383
1.57 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1259
20.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
11677
189.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
13595
220.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5985
6.98 IPS |
|
|
Pose Estimation (HP)
|
100% |
79646
92.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
80173
94.0 IPS |
|
|
Object Detection (SP)
|
100% |
1342
106.4 IPS |
|
|
Object Detection (HP)
|
99% |
10363
824.4 IPS |
|
|
Object Detection (Q)
|
91% |
11844
946.4 IPS |
|
|
Face Detection (SP)
|
100% |
2605
30.9 IPS |
|
|
Face Detection (HP)
|
100% |
25097
298.2 IPS |
|
|
Face Detection (Q)
|
100% |
37097
440.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5193
40.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
56930
438.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
62556
488.8 IPS |
|
|
Style Transfer (SP)
|
100% |
17289
22.2 IPS |
|
|
Style Transfer (HP)
|
100% |
143576
184.6 IPS |
|
|
Style Transfer (Q)
|
96% |
132219
170.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3636
134.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
28042
1.04 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
27743
1.02 KIPS |
|
|
Text Classification (SP)
|
100% |
2601
3.47 KIPS |
|
|
Text Classification (HP)
|
100% |
1478
1.97 KIPS |
|
|
Text Classification (Q)
|
93% |
1764
2.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3464
59.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6030
103.9 IPS |
|
|
Machine Translation (Q)
|
98% |
6767
116.9 IPS |
