iPhone 12 Mini
Geekbench AI Score
2762
Single Precision Score
11123
Half Precision Score
11087
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | sichunlam |
| Upload Date | August 15 2024 05:19 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A14 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1263
234.8 IPS |
|
|
Image Classification (HP)
|
100% |
4436
825.0 IPS |
|
|
Image Classification (Q)
|
99% |
5240
977.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1151
18.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
5456
88.4 IPS |
|
|
Image Segmentation (Q)
|
100% |
5301
85.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
5550
6.48 IPS |
|
|
Pose Estimation (HP)
|
100% |
58437
68.2 IPS |
|
|
Pose Estimation (Q)
|
94% |
59051
69.3 IPS |
|
|
Object Detection (SP)
|
100% |
1336
106.0 IPS |
|
|
Object Detection (HP)
|
99% |
5429
431.8 IPS |
|
|
Object Detection (Q)
|
91% |
4567
364.9 IPS |
|
|
Face Detection (SP)
|
100% |
2567
30.5 IPS |
|
|
Face Detection (HP)
|
100% |
11404
135.5 IPS |
|
|
Face Detection (Q)
|
100% |
11098
131.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
4891
37.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
34128
262.9 IPS |
|
|
Depth Estimation (Q)
|
97% |
36955
285.7 IPS |
|
|
Style Transfer (SP)
|
100% |
13619
17.5 IPS |
|
|
Style Transfer (HP)
|
100% |
103345
132.9 IPS |
|
|
Style Transfer (Q)
|
100% |
109976
141.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2918
107.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
19050
703.4 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
18093
670.3 IPS |
|
|
Text Classification (SP)
|
100% |
2117
2.83 KIPS |
|
|
Text Classification (HP)
|
100% |
2466
3.29 KIPS |
|
|
Text Classification (Q)
|
93% |
2304
3.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
2277
39.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1999
34.4 IPS |
|
|
Machine Translation (Q)
|
98% |
1994
34.5 IPS |
