iPhone 13 mini
Geekbench AI Score
3326
Single Precision Score
17040
Half Precision Score
18588
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | OoO |
| Upload Date | September 24 2024 06:49 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1365
253.9 IPS |
|
|
Image Classification (HP)
|
100% |
9367
1.74 KIPS |
|
|
Image Classification (Q)
|
96% |
10098
1.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1341
21.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
7322
118.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
7692
124.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6478
7.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
87292
101.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
93898
110.1 IPS |
|
|
Object Detection (SP)
|
100% |
1480
117.4 IPS |
|
|
Object Detection (HP)
|
99% |
10728
853.4 IPS |
|
|
Object Detection (Q)
|
91% |
11498
918.8 IPS |
|
|
Face Detection (SP)
|
100% |
2843
33.8 IPS |
|
|
Face Detection (HP)
|
100% |
26245
311.8 IPS |
|
|
Face Detection (Q)
|
100% |
32710
388.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
5555
42.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
53528
412.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
71490
558.7 IPS |
|
|
Style Transfer (SP)
|
100% |
17655
22.7 IPS |
|
|
Style Transfer (HP)
|
100% |
159197
204.7 IPS |
|
|
Style Transfer (Q)
|
96% |
157777
203.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3990
147.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27483
1.01 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
29348
1.08 KIPS |
|
|
Text Classification (SP)
|
100% |
2446
3.26 KIPS |
|
|
Text Classification (HP)
|
100% |
2311
3.08 KIPS |
|
|
Text Classification (Q)
|
93% |
2404
3.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
3475
59.9 IPS |
|
|
Machine Translation (HP)
|
100% |
2263
39.0 IPS |
|
|
Machine Translation (Q)
|
98% |
2256
39.0 IPS |
