iPhone 15 Pro
Geekbench ML Score
5993
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 04:03 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
1320
247.0 IPS |
|
|
Image Classification (F16)
|
100% |
6312
1.18 KIPS |
|
|
Image Classification (I8)
|
99% |
6875
1.29 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1491
24.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1865
31.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1903
31.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
15089
18.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
83252
100.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
84613
102.5 IPS |
|
|
Object Detection (F32)
|
100% |
1447
108.0 IPS |
|
|
Object Detection (F16)
|
100% |
4375
326.6 IPS |
|
|
Object Detection (I8)
|
97% |
1568
117.1 IPS |
|
|
Face Detection (F32)
|
100% |
6260
74.4 IPS |
|
|
Face Detection (F16)
|
97% |
10603
126.1 IPS |
|
|
Face Detection (I8)
|
96% |
10604
126.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12623
97.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
36943
286.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
42325
328.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29870
39.3 IPS |
|
|
Style Transfer (F16)
|
100% |
120525
158.5 IPS |
|
|
Style Transfer (I8)
|
100% |
120108
158.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6292
224.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18353
655.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16569
591.7 IPS |
|
|
Text Classification (F32)
|
100% |
478
686.9 IPS |
|
|
Text Classification (F16)
|
100% |
490
704.4 IPS |
|
|
Text Classification (I8)
|
96% |
302
434.5 IPS |
|
|
Machine Translation (F32)
|
100% |
750
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1555
28.6 IPS |
|
|
Machine Translation (I8)
|
99% |
705
13.0 IPS |
