iPhone 14 Pro
Geekbench ML Score
6119
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 26 2024 02:16 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 | 5.53 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
998
186.7 IPS |
|
|
Image Classification (F16)
|
100% |
5273
986.8 IPS |
|
|
Image Classification (I8)
|
99% |
5828
1.09 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1227
20.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1745
29.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1748
29.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
11490
13.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
81691
98.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
82816
100.3 IPS |
|
|
Object Detection (F32)
|
100% |
1421
106.1 IPS |
|
|
Object Detection (F16)
|
100% |
3644
272.1 IPS |
|
|
Object Detection (I8)
|
97% |
1389
103.7 IPS |
|
|
Face Detection (F32)
|
100% |
4915
58.4 IPS |
|
|
Face Detection (F16)
|
97% |
11726
139.4 IPS |
|
|
Face Detection (I8)
|
96% |
11850
140.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
8855
68.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
31666
245.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
35063
271.9 IPS |
|
|
Style Transfer (F32)
|
100% |
21085
27.7 IPS |
|
|
Style Transfer (F16)
|
100% |
111874
147.2 IPS |
|
|
Style Transfer (I8)
|
100% |
113158
148.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4353
155.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17188
613.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16884
603.0 IPS |
|
|
Text Classification (F32)
|
100% |
2440
3.51 KIPS |
|
|
Text Classification (F16)
|
100% |
1906
2.74 KIPS |
|
|
Text Classification (I8)
|
96% |
1896
2.72 KIPS |
|
|
Machine Translation (F32)
|
100% |
551
10.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1017
18.7 IPS |
|
|
Machine Translation (I8)
|
99% |
557
10.3 IPS |
