iPhone 13 mini
Geekbench AI Score
1846
Single Precision Score
10766
Half Precision Score
11180
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | fiwswe |
| Upload Date | August 16 2024 10:11 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| Model | iPhone 13 mini |
| Model ID | iPhone14,4 |
| Motherboard | D16AP |
| 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 | 3.55 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
944
175.5 IPS |
|
|
Image Classification (HP)
|
100% |
4503
837.5 IPS |
|
|
Image Classification (Q)
|
99% |
5180
966.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
633
10.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
3777
61.2 IPS |
|
|
Image Segmentation (Q)
|
100% |
3871
62.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
5379
6.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
72081
84.1 IPS |
|
|
Pose Estimation (Q)
|
94% |
60315
70.7 IPS |
|
|
Object Detection (SP)
|
100% |
929
73.7 IPS |
|
|
Object Detection (HP)
|
99% |
5780
459.8 IPS |
|
|
Object Detection (Q)
|
93% |
6822
544.4 IPS |
|
|
Face Detection (SP)
|
100% |
1590
18.9 IPS |
|
|
Face Detection (HP)
|
100% |
10260
121.9 IPS |
|
|
Face Detection (Q)
|
100% |
12014
142.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
3041
23.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
33791
260.3 IPS |
|
|
Depth Estimation (Q)
|
97% |
37906
293.1 IPS |
|
|
Style Transfer (SP)
|
100% |
8925
11.5 IPS |
|
|
Style Transfer (HP)
|
100% |
102036
131.2 IPS |
|
|
Style Transfer (Q)
|
100% |
103095
132.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2703
99.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
13278
490.3 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
15426
571.5 IPS |
|
|
Text Classification (SP)
|
100% |
998
1.33 KIPS |
|
|
Text Classification (HP)
|
100% |
3059
4.08 KIPS |
|
|
Text Classification (Q)
|
93% |
2490
3.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
1323
22.8 IPS |
|
|
Machine Translation (HP)
|
100% |
2056
35.4 IPS |
|
|
Machine Translation (Q)
|
98% |
2052
35.5 IPS |
