iPhone 13 Pro
Geekbench ML Score
4934
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 10 2024 09:29 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.1.2 |
| 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% |
1105
206.8 IPS |
|
|
Image Classification (F16)
|
100% |
5088
952.2 IPS |
|
|
Image Classification (I8)
|
99% |
4621
864.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
1190
19.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1576
26.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1570
26.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
10820
13.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
72107
87.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
70430
85.3 IPS |
|
|
Object Detection (F32)
|
100% |
1306
97.5 IPS |
|
|
Object Detection (F16)
|
100% |
3457
258.1 IPS |
|
|
Object Detection (I8)
|
97% |
1364
101.9 IPS |
|
|
Face Detection (F32)
|
100% |
4398
52.3 IPS |
|
|
Face Detection (F16)
|
97% |
9265
110.2 IPS |
|
|
Face Detection (I8)
|
96% |
9441
112.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
8643
67.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
33106
256.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
33374
258.8 IPS |
|
|
Style Transfer (F32)
|
100% |
18559
24.4 IPS |
|
|
Style Transfer (F16)
|
100% |
94024
123.7 IPS |
|
|
Style Transfer (I8)
|
100% |
97836
128.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3996
142.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14564
520.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15739
562.1 IPS |
|
|
Text Classification (F32)
|
100% |
392
563.4 IPS |
|
|
Text Classification (F16)
|
100% |
786
1.13 KIPS |
|
|
Text Classification (I8)
|
96% |
380
545.9 IPS |
|
|
Machine Translation (F32)
|
100% |
583
10.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1157
21.3 IPS |
|
|
Machine Translation (I8)
|
99% |
535
9.84 IPS |
