iPhone 15 Pro
Geekbench ML Score
3475
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 22 2024 06:34 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.3.1 |
| 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 | 7.50 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
766
143.4 IPS |
|
|
Image Classification (F16)
|
100% |
2808
525.5 IPS |
|
|
Image Classification (I8)
|
99% |
3290
615.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
839
14.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
930
15.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
917
15.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
9175
11.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
38841
47.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
39985
48.4 IPS |
|
|
Object Detection (F32)
|
100% |
1139
85.1 IPS |
|
|
Object Detection (F16)
|
100% |
2348
175.3 IPS |
|
|
Object Detection (I8)
|
97% |
1048
78.3 IPS |
|
|
Face Detection (F32)
|
100% |
5106
60.7 IPS |
|
|
Face Detection (F16)
|
97% |
5695
67.7 IPS |
|
|
Face Detection (I8)
|
96% |
5683
67.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
7989
62.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
24387
189.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
25298
196.2 IPS |
|
|
Style Transfer (F32)
|
100% |
23301
30.7 IPS |
|
|
Style Transfer (F16)
|
100% |
62301
82.0 IPS |
|
|
Style Transfer (I8)
|
100% |
60477
79.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3563
127.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10831
386.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10647
380.2 IPS |
|
|
Text Classification (F32)
|
100% |
350
502.6 IPS |
|
|
Text Classification (F16)
|
100% |
351
504.0 IPS |
|
|
Text Classification (I8)
|
96% |
250
359.8 IPS |
|
|
Machine Translation (F32)
|
100% |
402
7.39 IPS |
|
|
Machine Translation (F16)
|
100% |
683
12.6 IPS |
|
|
Machine Translation (I8)
|
99% |
339
6.25 IPS |
