iPhone 15 Pro Max
Geekbench ML Score
3645
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | karen_he |
| Upload Date | June 11 2024 07:10 PM |
| 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% |
1825
341.6 IPS |
|
|
Image Classification (F16)
|
100% |
1876
351.0 IPS |
|
|
Image Classification (I8)
|
99% |
1764
330.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1305
21.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1475
24.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1476
24.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
14565
17.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
15603
18.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
15551
18.8 IPS |
|
|
Object Detection (F32)
|
100% |
1595
119.1 IPS |
|
|
Object Detection (F16)
|
100% |
1801
134.4 IPS |
|
|
Object Detection (I8)
|
97% |
2018
150.7 IPS |
|
|
Face Detection (F32)
|
100% |
6282
74.7 IPS |
|
|
Face Detection (F16)
|
98% |
8350
99.3 IPS |
|
|
Face Detection (I8)
|
97% |
8568
101.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12261
95.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
13634
105.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
12793
99.2 IPS |
|
|
Style Transfer (F32)
|
100% |
28547
37.6 IPS |
|
|
Style Transfer (F16)
|
100% |
35835
47.1 IPS |
|
|
Style Transfer (I8)
|
100% |
36444
47.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6669
238.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4572
163.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6348
226.7 IPS |
|
|
Text Classification (F32)
|
100% |
464
667.0 IPS |
|
|
Text Classification (F16)
|
100% |
507
728.4 IPS |
|
|
Text Classification (I8)
|
96% |
308
442.6 IPS |
|
|
Machine Translation (F32)
|
100% |
742
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
784
14.4 IPS |
|
|
Machine Translation (I8)
|
99% |
693
12.7 IPS |
