iPhone 12 Mini
Geekbench AI Score
2741
Single Precision Score
12229
Half Precision Score
12159
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| User | Teva |
| Upload Date | January 26 2026 08:24 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A14 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.2 |
| Model | iPhone 12 Mini |
| Model ID | iPhone13,1 |
| Motherboard | D52gAP |
| CPU Information | |
|---|---|
| Name | Apple A14 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.99 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 3.61 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1211
225.2 IPS |
|
|
Image Classification (HP)
|
100% |
4630
861.0 IPS |
|
|
Image Classification (Q)
|
96% |
4491
838.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1114
18.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
7967
129.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
8681
140.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
5365
6.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
59365
69.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
60549
71.0 IPS |
|
|
Object Detection (SP)
|
100% |
1246
98.8 IPS |
|
|
Object Detection (HP)
|
99% |
5453
433.8 IPS |
|
|
Object Detection (Q)
|
91% |
4892
390.9 IPS |
|
|
Face Detection (SP)
|
100% |
2539
30.2 IPS |
|
|
Face Detection (HP)
|
100% |
12132
144.2 IPS |
|
|
Face Detection (Q)
|
100% |
10538
125.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
4889
37.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
37247
287.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
33644
262.9 IPS |
|
|
Style Transfer (SP)
|
100% |
14085
18.1 IPS |
|
|
Style Transfer (HP)
|
100% |
95145
122.3 IPS |
|
|
Style Transfer (Q)
|
96% |
92174
118.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2902
107.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
17581
649.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
18214
672.6 IPS |
|
|
Text Classification (SP)
|
100% |
2326
3.10 KIPS |
|
|
Text Classification (HP)
|
100% |
2294
3.06 KIPS |
|
|
Text Classification (Q)
|
93% |
2311
3.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
2253
38.8 IPS |
|
|
Machine Translation (HP)
|
100% |
3614
62.3 IPS |
|
|
Machine Translation (Q)
|
98% |
4449
76.9 IPS |
