iPhone 15 Pro
Geekbench ML Score
7654
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 19 2024 08:38 PM |
| Views | 11 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 | 7.51 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1519
284.3 IPS |
|
|
Image Classification (F16)
|
100% |
6031
1.13 KIPS |
|
|
Image Classification (I8)
|
99% |
6602
1.24 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1513
25.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1934
32.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1908
31.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
14813
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
87910
106.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
88285
106.9 IPS |
|
|
Object Detection (F32)
|
100% |
1665
124.3 IPS |
|
|
Object Detection (F16)
|
100% |
3914
292.2 IPS |
|
|
Object Detection (I8)
|
97% |
2103
157.0 IPS |
|
|
Face Detection (F32)
|
100% |
6108
72.6 IPS |
|
|
Face Detection (F16)
|
97% |
12768
151.8 IPS |
|
|
Face Detection (I8)
|
96% |
12719
151.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
12401
96.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
36007
279.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
33686
261.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29480
38.8 IPS |
|
|
Style Transfer (F16)
|
100% |
119206
156.8 IPS |
|
|
Style Transfer (I8)
|
100% |
116790
153.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7203
257.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17706
632.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17999
642.8 IPS |
|
|
Text Classification (F32)
|
100% |
2876
4.13 KIPS |
|
|
Text Classification (F16)
|
100% |
4873
7.00 KIPS |
|
|
Text Classification (I8)
|
96% |
4860
6.98 KIPS |
|
|
Machine Translation (F32)
|
100% |
638
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1575
29.0 IPS |
|
|
Machine Translation (I8)
|
99% |
644
11.8 IPS |
