iPhone 13 Pro
Geekbench ML Score
4994
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 02 2024 01:51 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.2.1 |
| Model | iPhone 13 Pro |
| Model ID | iPhone14,2 |
| Motherboard | D63AP |
| 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 | 5.51 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1177
220.2 IPS |
|
|
Image Classification (F16)
|
100% |
5110
956.3 IPS |
|
|
Image Classification (I8)
|
99% |
5826
1.09 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1101
18.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1458
24.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1515
25.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
10756
13.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
71990
87.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
75204
91.1 IPS |
|
|
Object Detection (F32)
|
100% |
1478
110.3 IPS |
|
|
Object Detection (F16)
|
100% |
3469
259.0 IPS |
|
|
Object Detection (I8)
|
97% |
1382
103.1 IPS |
|
|
Face Detection (F32)
|
100% |
4387
52.2 IPS |
|
|
Face Detection (F16)
|
97% |
9375
111.5 IPS |
|
|
Face Detection (I8)
|
96% |
9469
112.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
8539
66.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
32015
248.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
30540
236.8 IPS |
|
|
Style Transfer (F32)
|
100% |
18601
24.5 IPS |
|
|
Style Transfer (F16)
|
100% |
96948
127.5 IPS |
|
|
Style Transfer (I8)
|
100% |
98922
130.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3987
142.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14686
524.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
14779
527.8 IPS |
|
|
Text Classification (F32)
|
100% |
401
576.8 IPS |
|
|
Text Classification (F16)
|
100% |
900
1.29 KIPS |
|
|
Text Classification (I8)
|
96% |
392
563.4 IPS |
|
|
Machine Translation (F32)
|
100% |
587
10.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1139
21.0 IPS |
|
|
Machine Translation (I8)
|
99% |
540
9.94 IPS |
