iPhone 13 mini
Geekbench AI Score
3180
Single Precision Score
18774
Half Precision Score
20508
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | Swaddy |
| Upload Date | December 28 2025 09:23 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| 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% |
1264
235.1 IPS |
|
|
Image Classification (HP)
|
100% |
7584
1.41 KIPS |
|
|
Image Classification (Q)
|
96% |
10088
1.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1297
21.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
13658
221.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
12983
210.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6077
7.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
76785
89.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
82978
97.3 IPS |
|
|
Object Detection (SP)
|
100% |
1353
107.3 IPS |
|
|
Object Detection (HP)
|
99% |
10492
834.6 IPS |
|
|
Object Detection (Q)
|
91% |
11879
949.2 IPS |
|
|
Face Detection (SP)
|
100% |
2715
32.3 IPS |
|
|
Face Detection (HP)
|
100% |
28073
333.6 IPS |
|
|
Face Detection (Q)
|
100% |
35923
426.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5250
40.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
56305
433.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
75522
590.2 IPS |
|
|
Style Transfer (SP)
|
100% |
17377
22.3 IPS |
|
|
Style Transfer (HP)
|
100% |
145070
186.5 IPS |
|
|
Style Transfer (Q)
|
96% |
136236
175.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3612
133.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29539
1.09 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
27337
1.01 KIPS |
|
|
Text Classification (SP)
|
100% |
2533
3.38 KIPS |
|
|
Text Classification (HP)
|
100% |
1547
2.07 KIPS |
|
|
Text Classification (Q)
|
93% |
1388
1.86 KIPS |
|
|
Machine Translation (SP)
|
100% |
3463
59.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6221
107.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7270
125.6 IPS |
