iPhone 15 Pro
Geekbench ML Score
5958
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 04:30 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% |
1231
230.3 IPS |
|
|
Image Classification (F16)
|
100% |
6309
1.18 KIPS |
|
|
Image Classification (I8)
|
99% |
6812
1.27 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1450
24.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1841
30.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1864
31.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
14735
17.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
82675
100.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
85242
103.2 IPS |
|
|
Object Detection (F32)
|
100% |
1447
108.0 IPS |
|
|
Object Detection (F16)
|
100% |
3936
293.8 IPS |
|
|
Object Detection (I8)
|
97% |
1634
122.0 IPS |
|
|
Face Detection (F32)
|
100% |
6407
76.2 IPS |
|
|
Face Detection (F16)
|
97% |
10590
125.9 IPS |
|
|
Face Detection (I8)
|
96% |
10618
126.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
12474
96.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
38779
300.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
39340
305.1 IPS |
|
|
Style Transfer (F32)
|
100% |
29563
38.9 IPS |
|
|
Style Transfer (F16)
|
100% |
120441
158.4 IPS |
|
|
Style Transfer (I8)
|
100% |
123826
162.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7210
257.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17780
635.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17010
607.5 IPS |
|
|
Text Classification (F32)
|
100% |
457
657.1 IPS |
|
|
Text Classification (F16)
|
100% |
483
694.4 IPS |
|
|
Text Classification (I8)
|
96% |
305
437.7 IPS |
|
|
Machine Translation (F32)
|
100% |
754
13.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1547
28.5 IPS |
|
|
Machine Translation (I8)
|
99% |
681
12.5 IPS |
