iPhone 13
Geekbench ML Score
4799
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 22 2024 11:09 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.6.1 |
| 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 | 3.56 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
521
97.5 IPS |
|
|
Image Classification (F16)
|
100% |
5765
1.08 KIPS |
|
|
Image Classification (I8)
|
99% |
5675
1.06 KIPS |
|
|
Image Segmentation (F32)
|
100% |
547
9.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
2947
49.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
2982
49.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
9129
11.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
72678
88.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
77715
94.1 IPS |
|
|
Object Detection (F32)
|
100% |
703
52.5 IPS |
|
|
Object Detection (F16)
|
100% |
3435
256.5 IPS |
|
|
Object Detection (I8)
|
97% |
1164
86.9 IPS |
|
|
Face Detection (F32)
|
100% |
4255
50.6 IPS |
|
|
Face Detection (F16)
|
97% |
10710
127.3 IPS |
|
|
Face Detection (I8)
|
96% |
11009
130.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
6849
53.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
25741
199.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
24841
192.6 IPS |
|
|
Style Transfer (F32)
|
100% |
16696
22.0 IPS |
|
|
Style Transfer (F16)
|
100% |
89070
117.2 IPS |
|
|
Style Transfer (I8)
|
100% |
90745
119.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3035
108.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12153
434.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
11899
424.9 IPS |
|
|
Text Classification (F32)
|
100% |
400
575.2 IPS |
|
|
Text Classification (F16)
|
100% |
862
1.24 KIPS |
|
|
Text Classification (I8)
|
96% |
848
1.22 KIPS |
|
|
Machine Translation (F32)
|
100% |
756
13.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1115
20.5 IPS |
|
|
Machine Translation (I8)
|
99% |
718
13.2 IPS |
