iPhone 15 Pro Max
Geekbench ML Score
4474
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | Felixmac |
| Upload Date | July 06 2024 10:12 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 | 7.48 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1587
296.9 IPS |
|
|
Image Classification (F16)
|
100% |
2923
546.9 IPS |
|
|
Image Classification (I8)
|
99% |
2898
542.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
977
16.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1254
20.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1151
19.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
7022
8.50 IPS |
|
|
Pose Estimation (F16)
|
100% |
15457
18.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
15640
18.9 IPS |
|
|
Object Detection (F32)
|
100% |
1636
122.1 IPS |
|
|
Object Detection (F16)
|
100% |
2754
205.6 IPS |
|
|
Object Detection (I8)
|
97% |
1647
123.0 IPS |
|
|
Face Detection (F32)
|
100% |
2962
35.2 IPS |
|
|
Face Detection (F16)
|
97% |
6157
73.2 IPS |
|
|
Face Detection (I8)
|
97% |
5979
71.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
6573
51.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
13332
103.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
13013
100.9 IPS |
|
|
Style Transfer (F32)
|
100% |
20574
27.1 IPS |
|
|
Style Transfer (F16)
|
100% |
32711
43.0 IPS |
|
|
Style Transfer (I8)
|
100% |
32625
42.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5323
190.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6448
230.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6410
228.9 IPS |
|
|
Text Classification (F32)
|
100% |
2985
4.29 KIPS |
|
|
Text Classification (F16)
|
100% |
5199
7.47 KIPS |
|
|
Text Classification (I8)
|
96% |
5330
7.66 KIPS |
|
|
Machine Translation (F32)
|
100% |
1326
24.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1629
30.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1301
23.9 IPS |
