iPhone 13
Geekbench ML Score
4628
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | March 27 2024 07:03 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPhone 13 |
| Model ID | iPhone14,5 |
| Motherboard | D17AP |
| 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 | 3.54 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
642
120.2 IPS |
|
|
Image Classification (F16)
|
100% |
5164
966.4 IPS |
|
|
Image Classification (I8)
|
99% |
5035
942.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1183
19.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1685
28.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1689
28.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
8682
10.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
73081
88.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
60775
73.6 IPS |
|
|
Object Detection (F32)
|
100% |
1033
77.1 IPS |
|
|
Object Detection (F16)
|
100% |
3428
255.9 IPS |
|
|
Object Detection (I8)
|
97% |
1005
75.1 IPS |
|
|
Face Detection (F32)
|
100% |
3837
45.6 IPS |
|
|
Face Detection (F16)
|
97% |
9738
115.8 IPS |
|
|
Face Detection (I8)
|
96% |
9557
113.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
7743
60.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
35951
278.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
39389
305.5 IPS |
|
|
Style Transfer (F32)
|
100% |
16692
22.0 IPS |
|
|
Style Transfer (F16)
|
100% |
100992
132.8 IPS |
|
|
Style Transfer (I8)
|
100% |
97875
128.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3050
108.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14217
507.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
13629
486.7 IPS |
|
|
Text Classification (F32)
|
100% |
363
521.6 IPS |
|
|
Text Classification (F16)
|
100% |
1036
1.49 KIPS |
|
|
Text Classification (I8)
|
96% |
346
497.5 IPS |
|
|
Machine Translation (F32)
|
100% |
490
9.02 IPS |
|
|
Machine Translation (F16)
|
100% |
1100
20.2 IPS |
|
|
Machine Translation (I8)
|
99% |
444
8.18 IPS |
