iPhone 13 mini
Geekbench AI Score
3285
Single Precision Score
18994
Half Precision Score
22128
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Meinlsync |
| Upload Date | March 02 2025 10:04 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.3.1 |
| 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 | 3.59 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1337
248.7 IPS |
|
|
Image Classification (HP)
|
100% |
7915
1.47 KIPS |
|
|
Image Classification (Q)
|
96% |
9731
1.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1336
21.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
12993
210.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
15285
247.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6154
7.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
86609
101.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
93582
109.7 IPS |
|
|
Object Detection (SP)
|
100% |
1441
114.3 IPS |
|
|
Object Detection (HP)
|
99% |
10041
798.7 IPS |
|
|
Object Detection (Q)
|
91% |
11685
933.7 IPS |
|
|
Face Detection (SP)
|
100% |
2793
33.2 IPS |
|
|
Face Detection (HP)
|
100% |
28228
335.4 IPS |
|
|
Face Detection (Q)
|
100% |
35298
419.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
5417
41.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
54398
419.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
77525
605.8 IPS |
|
|
Style Transfer (SP)
|
100% |
17506
22.5 IPS |
|
|
Style Transfer (HP)
|
100% |
150805
193.9 IPS |
|
|
Style Transfer (Q)
|
96% |
149890
193.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3932
145.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
24844
917.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27220
1.01 KIPS |
|
|
Text Classification (SP)
|
100% |
2458
3.28 KIPS |
|
|
Text Classification (HP)
|
100% |
1968
2.63 KIPS |
|
|
Text Classification (Q)
|
93% |
2126
2.85 KIPS |
|
|
Machine Translation (SP)
|
100% |
3618
62.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6039
104.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7293
126.0 IPS |
