iPhone 15 Pro
Geekbench ML Score
5512
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 27 2024 08:06 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6 |
| 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% |
760
142.2 IPS |
|
|
Image Classification (F16)
|
100% |
6275
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6782
1.27 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1384
23.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1878
31.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1868
31.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
14848
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
82885
100.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
85787
103.9 IPS |
|
|
Object Detection (F32)
|
100% |
1440
107.5 IPS |
|
|
Object Detection (F16)
|
100% |
3812
284.6 IPS |
|
|
Object Detection (I8)
|
97% |
1337
99.8 IPS |
|
|
Face Detection (F32)
|
100% |
4217
50.1 IPS |
|
|
Face Detection (F16)
|
97% |
10608
126.1 IPS |
|
|
Face Detection (I8)
|
96% |
10572
125.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
11380
88.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
37712
292.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
39891
309.4 IPS |
|
|
Style Transfer (F32)
|
100% |
29638
39.0 IPS |
|
|
Style Transfer (F16)
|
100% |
122329
160.9 IPS |
|
|
Style Transfer (I8)
|
100% |
121014
159.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3554
126.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18148
648.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17441
622.9 IPS |
|
|
Text Classification (F32)
|
100% |
454
652.2 IPS |
|
|
Text Classification (F16)
|
100% |
491
705.9 IPS |
|
|
Text Classification (I8)
|
96% |
303
435.6 IPS |
|
|
Machine Translation (F32)
|
100% |
600
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1559
28.7 IPS |
|
|
Machine Translation (I8)
|
99% |
565
10.4 IPS |
