iPhone 13 mini
Geekbench ML Score
3306
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 06:59 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.55 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1394
260.9 IPS |
|
|
Image Classification (F16)
|
100% |
1742
326.0 IPS |
|
|
Image Classification (I8)
|
99% |
1742
326.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
824
13.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
823
13.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
822
13.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
5683
6.88 IPS |
|
|
Pose Estimation (F16)
|
100% |
13336
16.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
13273
16.1 IPS |
|
|
Object Detection (F32)
|
100% |
1368
102.2 IPS |
|
|
Object Detection (F16)
|
100% |
1903
142.1 IPS |
|
|
Object Detection (I8)
|
97% |
1387
103.5 IPS |
|
|
Face Detection (F32)
|
100% |
2476
29.4 IPS |
|
|
Face Detection (F16)
|
97% |
3976
47.3 IPS |
|
|
Face Detection (I8)
|
97% |
3864
45.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
4993
38.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
8079
62.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
8077
62.6 IPS |
|
|
Style Transfer (F32)
|
100% |
16292
21.4 IPS |
|
|
Style Transfer (F16)
|
100% |
24959
32.8 IPS |
|
|
Style Transfer (I8)
|
100% |
25096
33.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3751
134.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5036
179.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4916
175.6 IPS |
|
|
Text Classification (F32)
|
100% |
2216
3.18 KIPS |
|
|
Text Classification (F16)
|
100% |
3489
5.01 KIPS |
|
|
Text Classification (I8)
|
96% |
3477
5.00 KIPS |
|
|
Machine Translation (F32)
|
100% |
999
18.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1301
24.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1086
20.0 IPS |
