iPhone 14 Pro
Geekbench ML Score
4780
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 05:23 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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% |
699
130.8 IPS |
|
|
Image Classification (F16)
|
100% |
5318
995.1 IPS |
|
|
Image Classification (I8)
|
99% |
5819
1.09 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1155
19.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1666
27.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1692
28.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
11458
13.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
78545
95.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
81854
99.1 IPS |
|
|
Object Detection (F32)
|
100% |
972
72.6 IPS |
|
|
Object Detection (F16)
|
100% |
3855
287.8 IPS |
|
|
Object Detection (I8)
|
97% |
1191
88.9 IPS |
|
|
Face Detection (F32)
|
100% |
3888
46.2 IPS |
|
|
Face Detection (F16)
|
97% |
10038
119.4 IPS |
|
|
Face Detection (I8)
|
96% |
10109
120.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
8193
63.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
34510
267.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
38944
302.0 IPS |
|
|
Style Transfer (F32)
|
100% |
21160
27.8 IPS |
|
|
Style Transfer (F16)
|
100% |
114972
151.2 IPS |
|
|
Style Transfer (I8)
|
100% |
114943
151.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3483
124.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16490
588.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17104
610.8 IPS |
|
|
Text Classification (F32)
|
100% |
372
534.4 IPS |
|
|
Text Classification (F16)
|
100% |
359
516.6 IPS |
|
|
Text Classification (I8)
|
96% |
226
324.3 IPS |
|
|
Machine Translation (F32)
|
100% |
492
9.05 IPS |
|
|
Machine Translation (F16)
|
100% |
1145
21.1 IPS |
|
|
Machine Translation (I8)
|
99% |
514
9.46 IPS |
