iPhone 13 Pro
Geekbench AI Score
3269
Single Precision Score
19016
Half Precision Score
22153
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | March 25 2026 02:30 AM |
| Views | 8 |
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% |
1319
245.3 IPS |
|
|
Image Classification (HP)
|
100% |
7890
1.47 KIPS |
|
|
Image Classification (Q)
|
96% |
9680
1.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1286
20.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
12965
210.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
15635
253.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6265
7.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
91750
107.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
93347
109.4 IPS |
|
|
Object Detection (SP)
|
100% |
1448
114.8 IPS |
|
|
Object Detection (HP)
|
99% |
10366
824.6 IPS |
|
|
Object Detection (Q)
|
91% |
11852
947.0 IPS |
|
|
Face Detection (SP)
|
100% |
2718
32.3 IPS |
|
|
Face Detection (HP)
|
100% |
29318
348.4 IPS |
|
|
Face Detection (Q)
|
100% |
36513
433.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5380
41.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
56588
436.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
72890
569.6 IPS |
|
|
Style Transfer (SP)
|
100% |
17556
22.6 IPS |
|
|
Style Transfer (HP)
|
100% |
149944
192.8 IPS |
|
|
Style Transfer (Q)
|
96% |
160626
207.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3876
143.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
25906
956.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27462
1.01 KIPS |
|
|
Text Classification (SP)
|
100% |
2458
3.28 KIPS |
|
|
Text Classification (HP)
|
100% |
1629
2.17 KIPS |
|
|
Text Classification (Q)
|
93% |
2073
2.78 KIPS |
|
|
Machine Translation (SP)
|
100% |
3714
64.0 IPS |
|
|
Machine Translation (HP)
|
100% |
6056
104.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6987
120.7 IPS |
