iPhone 15 Pro Max
Geekbench ML Score
3998
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 09:52 AM |
| Views | 39 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| 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 | 7.44 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1689
316.0 IPS |
|
|
Image Classification (F16)
|
100% |
2135
399.6 IPS |
|
|
Image Classification (I8)
|
99% |
2163
404.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
869
14.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
840
14.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
842
14.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
7219
8.74 IPS |
|
|
Pose Estimation (F16)
|
100% |
15883
19.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
15892
19.2 IPS |
|
|
Object Detection (F32)
|
100% |
1628
121.6 IPS |
|
|
Object Detection (F16)
|
100% |
2268
169.3 IPS |
|
|
Object Detection (I8)
|
97% |
1638
122.3 IPS |
|
|
Face Detection (F32)
|
100% |
2794
33.2 IPS |
|
|
Face Detection (F16)
|
97% |
4649
55.3 IPS |
|
|
Face Detection (I8)
|
97% |
4648
55.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
6164
47.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
9529
73.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
9658
74.9 IPS |
|
|
Style Transfer (F32)
|
100% |
19806
26.1 IPS |
|
|
Style Transfer (F16)
|
100% |
29956
39.4 IPS |
|
|
Style Transfer (I8)
|
100% |
29989
39.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5097
182.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6481
231.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6098
217.8 IPS |
|
|
Text Classification (F32)
|
100% |
2930
4.21 KIPS |
|
|
Text Classification (F16)
|
100% |
4823
6.93 KIPS |
|
|
Text Classification (I8)
|
96% |
4817
6.92 KIPS |
|
|
Machine Translation (F32)
|
100% |
1305
24.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1562
28.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1270
23.4 IPS |
