iPhone 13 Pro
Geekbench AI Score
3170
Single Precision Score
18001
Half Precision Score
20489
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | October 21 2025 02:36 AM |
| Views | 8 |
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% |
1261
234.5 IPS |
|
|
Image Classification (HP)
|
100% |
7293
1.36 KIPS |
|
|
Image Classification (Q)
|
96% |
9067
1.69 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1265
20.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
13112
212.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
15309
248.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6051
7.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
76050
88.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
81741
95.8 IPS |
|
|
Object Detection (SP)
|
100% |
1356
107.6 IPS |
|
|
Object Detection (HP)
|
99% |
10384
826.0 IPS |
|
|
Object Detection (Q)
|
91% |
11749
938.8 IPS |
|
|
Face Detection (SP)
|
100% |
2636
31.3 IPS |
|
|
Face Detection (HP)
|
100% |
25195
299.4 IPS |
|
|
Face Detection (Q)
|
100% |
33023
392.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
5220
40.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
53190
409.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
66156
517.0 IPS |
|
|
Style Transfer (SP)
|
100% |
17429
22.4 IPS |
|
|
Style Transfer (HP)
|
100% |
145699
187.3 IPS |
|
|
Style Transfer (Q)
|
96% |
131515
169.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3665
135.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27339
1.01 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28066
1.04 KIPS |
|
|
Text Classification (SP)
|
100% |
2577
3.44 KIPS |
|
|
Text Classification (HP)
|
100% |
1461
1.95 KIPS |
|
|
Text Classification (Q)
|
93% |
1753
2.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
3464
59.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6067
104.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6919
119.6 IPS |
