iPhone 14 Pro
Geekbench ML Score
5120
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 04:27 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% |
1225
229.2 IPS |
|
|
Image Classification (F16)
|
100% |
5321
995.7 IPS |
|
|
Image Classification (I8)
|
99% |
5881
1.10 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1238
20.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1722
28.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1695
28.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
11459
13.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
78529
95.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
77826
94.2 IPS |
|
|
Object Detection (F32)
|
100% |
1393
104.0 IPS |
|
|
Object Detection (F16)
|
100% |
3729
278.4 IPS |
|
|
Object Detection (I8)
|
97% |
1379
103.0 IPS |
|
|
Face Detection (F32)
|
100% |
5095
60.6 IPS |
|
|
Face Detection (F16)
|
97% |
10087
119.9 IPS |
|
|
Face Detection (I8)
|
96% |
10033
119.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
8719
67.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
35988
279.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
37587
291.5 IPS |
|
|
Style Transfer (F32)
|
100% |
21252
28.0 IPS |
|
|
Style Transfer (F16)
|
100% |
115599
152.1 IPS |
|
|
Style Transfer (I8)
|
100% |
117555
154.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5035
179.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15463
552.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15972
570.4 IPS |
|
|
Text Classification (F32)
|
100% |
355
509.6 IPS |
|
|
Text Classification (F16)
|
100% |
357
512.4 IPS |
|
|
Text Classification (I8)
|
96% |
252
361.7 IPS |
|
|
Machine Translation (F32)
|
100% |
602
11.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1109
20.4 IPS |
|
|
Machine Translation (I8)
|
99% |
588
10.8 IPS |
