iPhone 14 Pro
Geekbench ML Score
5144
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 08:34 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
1276
238.7 IPS |
|
|
Image Classification (F16)
|
100% |
5563
1.04 KIPS |
|
|
Image Classification (I8)
|
99% |
6108
1.14 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1229
20.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1716
28.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1695
28.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
11250
13.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
76680
92.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
80081
97.0 IPS |
|
|
Object Detection (F32)
|
100% |
1398
104.4 IPS |
|
|
Object Detection (F16)
|
100% |
3928
293.2 IPS |
|
|
Object Detection (I8)
|
97% |
1458
108.9 IPS |
|
|
Face Detection (F32)
|
100% |
5153
61.3 IPS |
|
|
Face Detection (F16)
|
97% |
10238
121.7 IPS |
|
|
Face Detection (I8)
|
96% |
10231
121.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
8714
67.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
37107
287.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
36954
286.6 IPS |
|
|
Style Transfer (F32)
|
100% |
19923
26.2 IPS |
|
|
Style Transfer (F16)
|
100% |
114598
150.7 IPS |
|
|
Style Transfer (I8)
|
100% |
117832
155.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4889
174.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15064
538.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16394
585.5 IPS |
|
|
Text Classification (F32)
|
100% |
356
510.9 IPS |
|
|
Text Classification (F16)
|
100% |
357
512.7 IPS |
|
|
Text Classification (I8)
|
96% |
245
351.9 IPS |
|
|
Machine Translation (F32)
|
100% |
595
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1123
20.7 IPS |
|
|
Machine Translation (I8)
|
99% |
586
10.8 IPS |
