iPhone 15 Pro Max
Geekbench ML Score
3623
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 04:43 PM |
| Views | 1 |
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% |
1698
317.8 IPS |
|
|
Image Classification (F16)
|
100% |
1526
285.6 IPS |
|
|
Image Classification (I8)
|
99% |
1684
315.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1380
23.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1552
25.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1499
25.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
14837
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
15841
19.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
15466
18.7 IPS |
|
|
Object Detection (F32)
|
100% |
1593
119.0 IPS |
|
|
Object Detection (F16)
|
100% |
1582
118.1 IPS |
|
|
Object Detection (I8)
|
97% |
1836
137.1 IPS |
|
|
Face Detection (F32)
|
100% |
6127
72.9 IPS |
|
|
Face Detection (F16)
|
98% |
7962
94.7 IPS |
|
|
Face Detection (I8)
|
97% |
8206
97.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
12202
94.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
13816
107.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
12694
98.4 IPS |
|
|
Style Transfer (F32)
|
100% |
27828
36.6 IPS |
|
|
Style Transfer (F16)
|
100% |
32140
42.3 IPS |
|
|
Style Transfer (I8)
|
100% |
32920
43.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6712
239.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6725
240.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
7560
270.0 IPS |
|
|
Text Classification (F32)
|
100% |
462
664.6 IPS |
|
|
Text Classification (F16)
|
100% |
497
714.5 IPS |
|
|
Text Classification (I8)
|
96% |
310
444.8 IPS |
|
|
Machine Translation (F32)
|
100% |
748
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
806
14.8 IPS |
|
|
Machine Translation (I8)
|
99% |
680
12.5 IPS |
