iPhone 14 Pro
Geekbench ML Score
6095
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 18 2024 08:17 PM |
| Views | 1 |
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% |
1203
225.2 IPS |
|
|
Image Classification (F16)
|
100% |
5319
995.4 IPS |
|
|
Image Classification (I8)
|
99% |
5783
1.08 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1219
20.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1676
28.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1705
28.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
11490
13.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
79410
96.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
82339
99.7 IPS |
|
|
Object Detection (F32)
|
100% |
1476
110.2 IPS |
|
|
Object Detection (F16)
|
100% |
3687
275.3 IPS |
|
|
Object Detection (I8)
|
97% |
1419
105.9 IPS |
|
|
Face Detection (F32)
|
100% |
4876
58.0 IPS |
|
|
Face Detection (F16)
|
97% |
11555
137.4 IPS |
|
|
Face Detection (I8)
|
96% |
11685
138.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
8637
67.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
32120
249.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
32548
252.4 IPS |
|
|
Style Transfer (F32)
|
100% |
20961
27.6 IPS |
|
|
Style Transfer (F16)
|
100% |
108998
143.4 IPS |
|
|
Style Transfer (I8)
|
100% |
110730
145.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4419
157.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16914
604.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17159
612.8 IPS |
|
|
Text Classification (F32)
|
100% |
2397
3.44 KIPS |
|
|
Text Classification (F16)
|
100% |
1831
2.63 KIPS |
|
|
Text Classification (I8)
|
96% |
1819
2.61 KIPS |
|
|
Machine Translation (F32)
|
100% |
545
10.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1018
18.7 IPS |
|
|
Machine Translation (I8)
|
99% |
556
10.2 IPS |
