iPhone 15 Pro Max
Geekbench ML Score
3330
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 08:47 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2166
405.3 IPS |
|
|
Image Classification (F16)
|
100% |
1582
296.1 IPS |
|
|
Image Classification (I8)
|
99% |
1262
236.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
996
16.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
891
14.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
848
14.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
14952
18.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
15388
18.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
15309
18.5 IPS |
|
|
Object Detection (F32)
|
100% |
2220
165.8 IPS |
|
|
Object Detection (F16)
|
100% |
1647
123.0 IPS |
|
|
Object Detection (I8)
|
97% |
1883
140.6 IPS |
|
|
Face Detection (F32)
|
100% |
6522
77.5 IPS |
|
|
Face Detection (F16)
|
98% |
7841
93.2 IPS |
|
|
Face Detection (I8)
|
97% |
7705
91.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
12760
99.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
14181
110.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
12966
100.5 IPS |
|
|
Style Transfer (F32)
|
100% |
29908
39.3 IPS |
|
|
Style Transfer (F16)
|
100% |
32966
43.4 IPS |
|
|
Style Transfer (I8)
|
100% |
36087
47.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4630
165.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5025
179.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4977
177.7 IPS |
|
|
Text Classification (F32)
|
100% |
481
690.6 IPS |
|
|
Text Classification (F16)
|
100% |
520
747.0 IPS |
|
|
Text Classification (I8)
|
96% |
481
691.5 IPS |
|
|
Machine Translation (F32)
|
100% |
509
9.37 IPS |
|
|
Machine Translation (F16)
|
100% |
560
10.3 IPS |
|
|
Machine Translation (I8)
|
99% |
458
8.44 IPS |
