iPhone 15 Pro Max
Geekbench ML Score
4601
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 04:18 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 | 7.48 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1743
326.1 IPS |
|
|
Image Classification (F16)
|
100% |
1748
327.1 IPS |
|
|
Image Classification (I8)
|
99% |
1800
336.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1392
23.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1580
26.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1558
26.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
14625
17.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
15540
18.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
15111
18.3 IPS |
|
|
Object Detection (F32)
|
100% |
1622
121.1 IPS |
|
|
Object Detection (F16)
|
100% |
1569
117.1 IPS |
|
|
Object Detection (I8)
|
97% |
1736
129.6 IPS |
|
|
Face Detection (F32)
|
100% |
6259
74.4 IPS |
|
|
Face Detection (F16)
|
98% |
8362
99.4 IPS |
|
|
Face Detection (I8)
|
97% |
8670
103.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12173
94.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
13679
106.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
12667
98.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29500
38.8 IPS |
|
|
Style Transfer (F16)
|
100% |
32824
43.2 IPS |
|
|
Style Transfer (I8)
|
100% |
36015
47.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6933
247.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7702
275.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
7550
269.6 IPS |
|
|
Text Classification (F32)
|
100% |
2929
4.21 KIPS |
|
|
Text Classification (F16)
|
100% |
5238
7.53 KIPS |
|
|
Text Classification (I8)
|
96% |
5106
7.34 KIPS |
|
|
Machine Translation (F32)
|
100% |
629
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
633
11.7 IPS |
|
|
Machine Translation (I8)
|
99% |
646
11.9 IPS |
