iPhone 15 Pro Max
Geekbench ML Score
3555
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 26 2024 02:37 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% |
1185
221.7 IPS |
|
|
Image Classification (F16)
|
100% |
1438
269.2 IPS |
|
|
Image Classification (I8)
|
99% |
1814
339.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1408
23.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1567
26.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1561
26.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
14847
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
15735
19.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
15562
18.8 IPS |
|
|
Object Detection (F32)
|
100% |
1517
113.2 IPS |
|
|
Object Detection (F16)
|
100% |
1509
112.7 IPS |
|
|
Object Detection (I8)
|
97% |
1534
114.5 IPS |
|
|
Face Detection (F32)
|
100% |
5757
68.5 IPS |
|
|
Face Detection (F16)
|
98% |
7996
95.1 IPS |
|
|
Face Detection (I8)
|
97% |
8320
98.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12422
96.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
13747
106.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
12659
98.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29537
38.9 IPS |
|
|
Style Transfer (F16)
|
100% |
31824
41.9 IPS |
|
|
Style Transfer (I8)
|
100% |
31190
41.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7037
251.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7182
256.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
7369
263.2 IPS |
|
|
Text Classification (F32)
|
100% |
480
689.5 IPS |
|
|
Text Classification (F16)
|
100% |
491
705.8 IPS |
|
|
Text Classification (I8)
|
96% |
298
428.4 IPS |
|
|
Machine Translation (F32)
|
100% |
742
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
782
14.4 IPS |
|
|
Machine Translation (I8)
|
99% |
672
12.4 IPS |
