iPhone 15 Pro
Geekbench ML Score
7544
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 07:15 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 | 7.51 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1200
224.6 IPS |
|
|
Image Classification (F16)
|
100% |
6218
1.16 KIPS |
|
|
Image Classification (I8)
|
99% |
6755
1.26 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1438
24.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1821
30.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1688
28.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
14898
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
87934
106.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
89194
108.0 IPS |
|
|
Object Detection (F32)
|
100% |
1517
113.2 IPS |
|
|
Object Detection (F16)
|
100% |
4158
310.4 IPS |
|
|
Object Detection (I8)
|
97% |
1659
123.9 IPS |
|
|
Face Detection (F32)
|
100% |
6246
74.3 IPS |
|
|
Face Detection (F16)
|
97% |
12814
152.4 IPS |
|
|
Face Detection (I8)
|
96% |
12764
151.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
12388
96.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
35147
272.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
36170
280.5 IPS |
|
|
Style Transfer (F32)
|
100% |
29812
39.2 IPS |
|
|
Style Transfer (F16)
|
100% |
112748
148.3 IPS |
|
|
Style Transfer (I8)
|
100% |
117148
154.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7143
255.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18306
653.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17825
636.6 IPS |
|
|
Text Classification (F32)
|
100% |
2941
4.23 KIPS |
|
|
Text Classification (F16)
|
100% |
5292
7.61 KIPS |
|
|
Text Classification (I8)
|
96% |
5053
7.26 KIPS |
|
|
Machine Translation (F32)
|
100% |
649
11.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1625
29.9 IPS |
|
|
Machine Translation (I8)
|
99% |
639
11.8 IPS |
