iPhone 15 Pro Max
Geekbench ML Score
4045
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 26 2024 05:03 PM |
| 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% |
1700
318.1 IPS |
|
|
Image Classification (F16)
|
100% |
2162
404.5 IPS |
|
|
Image Classification (I8)
|
99% |
2168
405.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
898
15.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
870
14.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
865
14.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
7394
8.95 IPS |
|
|
Pose Estimation (F16)
|
100% |
16089
19.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
16216
19.6 IPS |
|
|
Object Detection (F32)
|
100% |
1641
122.5 IPS |
|
|
Object Detection (F16)
|
100% |
2264
169.0 IPS |
|
|
Object Detection (I8)
|
97% |
1632
121.9 IPS |
|
|
Face Detection (F32)
|
100% |
2845
33.8 IPS |
|
|
Face Detection (F16)
|
97% |
4771
56.7 IPS |
|
|
Face Detection (I8)
|
97% |
4766
56.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
6240
48.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
9695
75.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
9632
74.7 IPS |
|
|
Style Transfer (F32)
|
100% |
20228
26.6 IPS |
|
|
Style Transfer (F16)
|
100% |
30154
39.7 IPS |
|
|
Style Transfer (I8)
|
100% |
30295
39.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5091
181.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6205
221.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6226
222.4 IPS |
|
|
Text Classification (F32)
|
100% |
2941
4.23 KIPS |
|
|
Text Classification (F16)
|
100% |
4852
6.97 KIPS |
|
|
Text Classification (I8)
|
96% |
4841
6.96 KIPS |
|
|
Machine Translation (F32)
|
100% |
1320
24.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1588
29.2 IPS |
|
|
Machine Translation (I8)
|
99% |
1292
23.8 IPS |
