iPhone 14 Pro
Geekbench ML Score
5173
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 26 2024 05:39 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 14 Pro |
| Model ID | iPhone15,2 |
| Motherboard | D73AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 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 | 5.50 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1033
193.3 IPS |
|
|
Image Classification (F16)
|
100% |
5414
1.01 KIPS |
|
|
Image Classification (I8)
|
99% |
5743
1.07 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1243
20.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1662
27.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1744
29.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
10977
13.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
78828
95.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
81202
98.3 IPS |
|
|
Object Detection (F32)
|
100% |
1829
136.6 IPS |
|
|
Object Detection (F16)
|
100% |
3798
283.5 IPS |
|
|
Object Detection (I8)
|
97% |
1436
107.2 IPS |
|
|
Face Detection (F32)
|
100% |
5172
61.5 IPS |
|
|
Face Detection (F16)
|
97% |
10346
123.0 IPS |
|
|
Face Detection (I8)
|
96% |
10208
121.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
8562
66.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
38998
302.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
36008
279.2 IPS |
|
|
Style Transfer (F32)
|
100% |
20111
26.5 IPS |
|
|
Style Transfer (F16)
|
100% |
118825
156.3 IPS |
|
|
Style Transfer (I8)
|
100% |
117361
154.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4309
153.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17307
618.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15851
566.1 IPS |
|
|
Text Classification (F32)
|
100% |
361
519.3 IPS |
|
|
Text Classification (F16)
|
100% |
354
509.2 IPS |
|
|
Text Classification (I8)
|
96% |
303
435.4 IPS |
|
|
Machine Translation (F32)
|
100% |
597
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1080
19.9 IPS |
|
|
Machine Translation (I8)
|
99% |
588
10.8 IPS |
