iPhone 15 Pro
Geekbench ML Score
6014
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 10 2024 08:13 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 15 Pro |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 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 | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1720
321.9 IPS |
|
|
Image Classification (F16)
|
100% |
6247
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6779
1.27 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1470
24.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1871
31.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1888
31.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
14907
18.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
82222
99.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
85186
103.2 IPS |
|
|
Object Detection (F32)
|
100% |
1459
108.9 IPS |
|
|
Object Detection (F16)
|
100% |
4065
303.5 IPS |
|
|
Object Detection (I8)
|
97% |
1619
120.9 IPS |
|
|
Face Detection (F32)
|
100% |
6259
74.4 IPS |
|
|
Face Detection (F16)
|
97% |
10622
126.3 IPS |
|
|
Face Detection (I8)
|
96% |
10583
125.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
12517
97.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
36288
281.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
37099
287.7 IPS |
|
|
Style Transfer (F32)
|
100% |
29760
39.1 IPS |
|
|
Style Transfer (F16)
|
100% |
120069
157.9 IPS |
|
|
Style Transfer (I8)
|
100% |
119742
157.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7163
255.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18607
664.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16844
601.5 IPS |
|
|
Text Classification (F32)
|
100% |
455
654.4 IPS |
|
|
Text Classification (F16)
|
100% |
479
688.8 IPS |
|
|
Text Classification (I8)
|
96% |
308
443.0 IPS |
|
|
Machine Translation (F32)
|
100% |
765
14.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1547
28.5 IPS |
|
|
Machine Translation (I8)
|
99% |
692
12.7 IPS |
