iPhone 14 Pro
Geekbench ML Score
5073
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 07 2024 12:29 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% |
1045
195.5 IPS |
|
|
Image Classification (F16)
|
100% |
5361
1.00 KIPS |
|
|
Image Classification (I8)
|
99% |
5727
1.07 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1222
20.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1666
27.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1673
27.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
11474
13.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
79416
96.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
67001
81.1 IPS |
|
|
Object Detection (F32)
|
100% |
1444
107.8 IPS |
|
|
Object Detection (F16)
|
100% |
3715
277.3 IPS |
|
|
Object Detection (I8)
|
97% |
1443
107.7 IPS |
|
|
Face Detection (F32)
|
100% |
5172
61.5 IPS |
|
|
Face Detection (F16)
|
97% |
10220
121.5 IPS |
|
|
Face Detection (I8)
|
96% |
10493
124.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
8800
68.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
35506
275.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
43688
338.8 IPS |
|
|
Style Transfer (F32)
|
100% |
21087
27.7 IPS |
|
|
Style Transfer (F16)
|
100% |
116764
153.6 IPS |
|
|
Style Transfer (I8)
|
100% |
119362
157.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4359
155.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16555
591.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15822
565.0 IPS |
|
|
Text Classification (F32)
|
100% |
362
520.4 IPS |
|
|
Text Classification (F16)
|
100% |
347
498.7 IPS |
|
|
Text Classification (I8)
|
96% |
238
341.3 IPS |
|
|
Machine Translation (F32)
|
100% |
595
10.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1066
19.6 IPS |
|
|
Machine Translation (I8)
|
99% |
581
10.7 IPS |
