iPhone 13
Geekbench ML Score
4587
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 18 2024 09:17 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6 |
| 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% |
584
109.2 IPS |
|
|
Image Classification (F16)
|
100% |
4917
920.1 IPS |
|
|
Image Classification (I8)
|
99% |
5872
1.10 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1151
19.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1683
28.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1731
28.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
9034
10.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
75460
91.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
76676
92.9 IPS |
|
|
Object Detection (F32)
|
100% |
812
60.6 IPS |
|
|
Object Detection (F16)
|
100% |
3442
256.9 IPS |
|
|
Object Detection (I8)
|
97% |
705
52.7 IPS |
|
|
Face Detection (F32)
|
100% |
2935
34.9 IPS |
|
|
Face Detection (F16)
|
97% |
9725
115.6 IPS |
|
|
Face Detection (I8)
|
96% |
9792
116.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
6166
47.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
34235
265.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
33825
262.3 IPS |
|
|
Style Transfer (F32)
|
100% |
16657
21.9 IPS |
|
|
Style Transfer (F16)
|
100% |
107906
141.9 IPS |
|
|
Style Transfer (I8)
|
100% |
101583
133.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3077
109.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14279
509.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15203
543.0 IPS |
|
|
Text Classification (F32)
|
100% |
574
825.6 IPS |
|
|
Text Classification (F16)
|
100% |
874
1.26 KIPS |
|
|
Text Classification (I8)
|
96% |
346
496.6 IPS |
|
|
Machine Translation (F32)
|
100% |
524
9.64 IPS |
|
|
Machine Translation (F16)
|
100% |
1150
21.2 IPS |
|
|
Machine Translation (I8)
|
99% |
476
8.76 IPS |
