iPhone 15 Pro Max
Geekbench ML Score
4016
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 29 2024 08:16 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1676
313.7 IPS |
|
|
Image Classification (F16)
|
100% |
2162
404.6 IPS |
|
|
Image Classification (I8)
|
99% |
2157
403.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
865
14.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
835
13.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
838
14.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
7292
8.83 IPS |
|
|
Pose Estimation (F16)
|
100% |
15878
19.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
16078
19.5 IPS |
|
|
Object Detection (F32)
|
100% |
1645
122.8 IPS |
|
|
Object Detection (F16)
|
100% |
2267
169.2 IPS |
|
|
Object Detection (I8)
|
97% |
1642
122.6 IPS |
|
|
Face Detection (F32)
|
100% |
2822
33.5 IPS |
|
|
Face Detection (F16)
|
97% |
4707
56.0 IPS |
|
|
Face Detection (I8)
|
97% |
4706
56.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
6250
48.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
9644
74.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
9706
75.3 IPS |
|
|
Style Transfer (F32)
|
100% |
20257
26.6 IPS |
|
|
Style Transfer (F16)
|
100% |
30088
39.6 IPS |
|
|
Style Transfer (I8)
|
100% |
30091
39.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5136
183.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5922
211.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6451
230.4 IPS |
|
|
Text Classification (F32)
|
100% |
2939
4.22 KIPS |
|
|
Text Classification (F16)
|
100% |
4894
7.03 KIPS |
|
|
Text Classification (I8)
|
96% |
4912
7.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
1310
24.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1570
28.9 IPS |
|
|
Machine Translation (I8)
|
99% |
1264
23.3 IPS |
