iPhone 15 Pro Max
Geekbench ML Score
6050
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | theBITFORCE |
| Upload Date | August 16 2024 02:43 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1654
309.5 IPS |
|
|
Image Classification (F16)
|
100% |
6245
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
7199
1.35 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1305
21.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1772
29.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1782
29.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
14457
17.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
82599
100.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
85210
103.2 IPS |
|
|
Object Detection (F32)
|
100% |
1469
109.7 IPS |
|
|
Object Detection (F16)
|
100% |
4049
302.3 IPS |
|
|
Object Detection (I8)
|
97% |
2266
169.2 IPS |
|
|
Face Detection (F32)
|
100% |
6345
75.4 IPS |
|
|
Face Detection (F16)
|
97% |
10638
126.5 IPS |
|
|
Face Detection (I8)
|
96% |
10446
124.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
12101
93.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
38344
297.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
45514
353.0 IPS |
|
|
Style Transfer (F32)
|
100% |
28284
37.2 IPS |
|
|
Style Transfer (F16)
|
100% |
119849
157.7 IPS |
|
|
Style Transfer (I8)
|
100% |
120303
158.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6762
241.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17255
616.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18497
660.6 IPS |
|
|
Text Classification (F32)
|
100% |
454
652.5 IPS |
|
|
Text Classification (F16)
|
100% |
485
697.5 IPS |
|
|
Text Classification (I8)
|
96% |
300
431.6 IPS |
|
|
Machine Translation (F32)
|
100% |
745
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1545
28.4 IPS |
|
|
Machine Translation (I8)
|
99% |
679
12.5 IPS |
