iPhone 15 Pro Max
Geekbench ML Score
3535
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 08 2024 01:14 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.2.1 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1646
308.0 IPS |
|
|
Image Classification (F16)
|
100% |
1640
306.8 IPS |
|
|
Image Classification (I8)
|
99% |
1508
282.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1362
22.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1523
25.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1527
25.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
14775
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
15835
19.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
15490
18.8 IPS |
|
|
Object Detection (F32)
|
100% |
1477
110.3 IPS |
|
|
Object Detection (F16)
|
100% |
1506
112.4 IPS |
|
|
Object Detection (I8)
|
97% |
1533
114.5 IPS |
|
|
Face Detection (F32)
|
100% |
6059
72.0 IPS |
|
|
Face Detection (F16)
|
97% |
8178
97.2 IPS |
|
|
Face Detection (I8)
|
96% |
8281
98.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
12311
95.5 IPS |
|
|
Depth Estimation (F16)
|
94% |
13787
106.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
12591
97.6 IPS |
|
|
Style Transfer (F32)
|
100% |
29328
38.6 IPS |
|
|
Style Transfer (F16)
|
100% |
32379
42.6 IPS |
|
|
Style Transfer (I8)
|
100% |
31331
41.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6507
232.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7530
268.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6948
248.1 IPS |
|
|
Text Classification (F32)
|
100% |
436
626.3 IPS |
|
|
Text Classification (F16)
|
100% |
446
640.7 IPS |
|
|
Text Classification (I8)
|
96% |
279
400.7 IPS |
|
|
Machine Translation (F32)
|
100% |
726
13.4 IPS |
|
|
Machine Translation (F16)
|
100% |
776
14.3 IPS |
|
|
Machine Translation (I8)
|
99% |
657
12.1 IPS |
