iPhone 15 Pro Max
Geekbench ML Score
2506
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 20 2024 08:46 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.1 |
| 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 | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1452
271.8 IPS |
|
|
Image Classification (F16)
|
100% |
1253
234.5 IPS |
|
|
Image Classification (I8)
|
99% |
1253
234.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
640
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
576
9.61 IPS |
|
|
Image Segmentation (I8)
|
100% |
563
9.41 IPS |
|
|
Pose Estimation (F32)
|
100% |
7404
8.97 IPS |
|
|
Pose Estimation (F16)
|
100% |
13890
16.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
13774
16.7 IPS |
|
|
Object Detection (F32)
|
100% |
1423
106.3 IPS |
|
|
Object Detection (F16)
|
100% |
1411
105.4 IPS |
|
|
Object Detection (I8)
|
97% |
1460
109.0 IPS |
|
|
Face Detection (F32)
|
100% |
2348
27.9 IPS |
|
|
Face Detection (F16)
|
100% |
2067
24.6 IPS |
|
|
Face Detection (I8)
|
99% |
2045
24.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
4770
37.0 IPS |
|
|
Depth Estimation (F16)
|
99% |
4997
38.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
5023
39.0 IPS |
|
|
Style Transfer (F32)
|
100% |
12922
17.0 IPS |
|
|
Style Transfer (F16)
|
100% |
15143
19.9 IPS |
|
|
Style Transfer (I8)
|
100% |
15208
20.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4375
156.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3667
131.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
3683
131.5 IPS |
|
|
Text Classification (F32)
|
100% |
1693
2.43 KIPS |
|
|
Text Classification (F16)
|
100% |
1069
1.54 KIPS |
|
|
Text Classification (I8)
|
96% |
1071
1.54 KIPS |
|
|
Machine Translation (F32)
|
100% |
1048
19.3 IPS |
|
|
Machine Translation (F16)
|
99% |
1104
20.3 IPS |
|
|
Machine Translation (I8)
|
99% |
1021
18.8 IPS |
