iPhone 13
Geekbench ML Score
4661
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 25 2024 04:00 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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% |
657
123.0 IPS |
|
|
Image Classification (F16)
|
100% |
5079
950.4 IPS |
|
|
Image Classification (I8)
|
99% |
5206
974.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1117
18.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1719
28.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1628
27.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
8773
10.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
71899
87.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
74498
90.2 IPS |
|
|
Object Detection (F32)
|
100% |
1092
81.5 IPS |
|
|
Object Detection (F16)
|
100% |
3606
269.2 IPS |
|
|
Object Detection (I8)
|
97% |
1014
75.7 IPS |
|
|
Face Detection (F32)
|
100% |
4059
48.3 IPS |
|
|
Face Detection (F16)
|
97% |
9782
116.3 IPS |
|
|
Face Detection (I8)
|
96% |
9811
116.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
7728
59.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
33972
263.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
34949
271.0 IPS |
|
|
Style Transfer (F32)
|
100% |
16616
21.9 IPS |
|
|
Style Transfer (F16)
|
100% |
97066
127.7 IPS |
|
|
Style Transfer (I8)
|
100% |
99420
130.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3085
110.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14396
514.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15184
542.3 IPS |
|
|
Text Classification (F32)
|
100% |
359
515.9 IPS |
|
|
Text Classification (F16)
|
100% |
837
1.20 KIPS |
|
|
Text Classification (I8)
|
96% |
335
481.0 IPS |
|
|
Machine Translation (F32)
|
100% |
524
9.64 IPS |
|
|
Machine Translation (F16)
|
100% |
1158
21.3 IPS |
|
|
Machine Translation (I8)
|
99% |
474
8.72 IPS |
