iPhone 15 Pro
Geekbench ML Score
3582
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 27 2024 03:16 AM |
| Views | 3 |
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% |
887
166.0 IPS |
|
|
Image Classification (F16)
|
100% |
2787
521.5 IPS |
|
|
Image Classification (I8)
|
99% |
3300
617.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
846
14.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
885
14.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
913
15.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
13668
16.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
38834
47.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
39849
48.3 IPS |
|
|
Object Detection (F32)
|
100% |
1100
82.2 IPS |
|
|
Object Detection (F16)
|
100% |
2355
175.9 IPS |
|
|
Object Detection (I8)
|
97% |
1052
78.6 IPS |
|
|
Face Detection (F32)
|
100% |
4087
48.6 IPS |
|
|
Face Detection (F16)
|
97% |
5631
66.9 IPS |
|
|
Face Detection (I8)
|
96% |
5675
67.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
8316
64.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
24511
190.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
25592
198.5 IPS |
|
|
Style Transfer (F32)
|
100% |
23538
31.0 IPS |
|
|
Style Transfer (F16)
|
100% |
62742
82.5 IPS |
|
|
Style Transfer (I8)
|
100% |
61417
80.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3817
136.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10730
383.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10873
388.3 IPS |
|
|
Text Classification (F32)
|
100% |
379
544.4 IPS |
|
|
Text Classification (F16)
|
100% |
402
577.1 IPS |
|
|
Text Classification (I8)
|
96% |
274
393.9 IPS |
|
|
Machine Translation (F32)
|
100% |
422
7.76 IPS |
|
|
Machine Translation (F16)
|
100% |
687
12.6 IPS |
|
|
Machine Translation (I8)
|
99% |
396
7.29 IPS |
