iPhone 15 Pro Max
Geekbench ML Score
3749
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 16 2024 09:05 AM |
| Views | 2 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1689
316.0 IPS |
|
|
Image Classification (F16)
|
100% |
1261
236.0 IPS |
|
|
Image Classification (I8)
|
99% |
1673
313.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1402
23.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1555
26.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1540
25.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
14369
17.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
15287
18.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
15426
18.7 IPS |
|
|
Object Detection (F32)
|
100% |
2354
175.7 IPS |
|
|
Object Detection (F16)
|
100% |
1549
115.6 IPS |
|
|
Object Detection (I8)
|
97% |
1949
145.5 IPS |
|
|
Face Detection (F32)
|
100% |
6452
76.7 IPS |
|
|
Face Detection (F16)
|
98% |
8330
99.0 IPS |
|
|
Face Detection (I8)
|
97% |
8669
103.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12220
94.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
13687
106.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
12758
98.9 IPS |
|
|
Style Transfer (F32)
|
100% |
28269
37.2 IPS |
|
|
Style Transfer (F16)
|
100% |
34882
45.9 IPS |
|
|
Style Transfer (I8)
|
100% |
35872
47.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6962
248.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7475
266.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
7382
263.6 IPS |
|
|
Text Classification (F32)
|
100% |
443
636.0 IPS |
|
|
Text Classification (F16)
|
100% |
538
772.8 IPS |
|
|
Text Classification (I8)
|
96% |
448
643.6 IPS |
|
|
Machine Translation (F32)
|
100% |
739
13.6 IPS |
|
|
Machine Translation (F16)
|
100% |
783
14.4 IPS |
|
|
Machine Translation (I8)
|
99% |
691
12.7 IPS |
