iPhone 15 Pro
Geekbench ML Score
6085
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 10 2024 07:07 PM |
| Views | 1 |
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% |
1465
274.1 IPS |
|
|
Image Classification (F16)
|
100% |
6296
1.18 KIPS |
|
|
Image Classification (I8)
|
99% |
6895
1.29 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1434
24.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1865
31.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1882
31.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
14857
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
83385
101.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
86234
104.4 IPS |
|
|
Object Detection (F32)
|
100% |
1823
136.1 IPS |
|
|
Object Detection (F16)
|
100% |
3950
294.9 IPS |
|
|
Object Detection (I8)
|
97% |
1560
116.5 IPS |
|
|
Face Detection (F32)
|
100% |
6402
76.1 IPS |
|
|
Face Detection (F16)
|
97% |
10644
126.6 IPS |
|
|
Face Detection (I8)
|
96% |
10617
126.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
12545
97.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
39352
305.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
42615
330.5 IPS |
|
|
Style Transfer (F32)
|
100% |
29532
38.8 IPS |
|
|
Style Transfer (F16)
|
100% |
120992
159.2 IPS |
|
|
Style Transfer (I8)
|
100% |
121679
160.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7197
257.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18022
643.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18609
664.6 IPS |
|
|
Text Classification (F32)
|
100% |
461
663.1 IPS |
|
|
Text Classification (F16)
|
100% |
488
701.3 IPS |
|
|
Text Classification (I8)
|
96% |
302
434.6 IPS |
|
|
Machine Translation (F32)
|
100% |
757
13.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1560
28.7 IPS |
|
|
Machine Translation (I8)
|
99% |
687
12.6 IPS |
