iPhone 15 Pro Max
Geekbench ML Score
6009
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 07:09 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| 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% |
1398
261.5 IPS |
|
|
Image Classification (F16)
|
100% |
6246
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6704
1.25 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1423
23.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1774
29.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1790
29.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
14769
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
82795
100.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
83173
100.7 IPS |
|
|
Object Detection (F32)
|
100% |
1471
109.8 IPS |
|
|
Object Detection (F16)
|
100% |
3887
290.2 IPS |
|
|
Object Detection (I8)
|
97% |
1733
129.4 IPS |
|
|
Face Detection (F32)
|
100% |
6151
73.1 IPS |
|
|
Face Detection (F16)
|
97% |
10564
125.6 IPS |
|
|
Face Detection (I8)
|
96% |
10616
126.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
12264
95.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
37383
289.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
40032
310.5 IPS |
|
|
Style Transfer (F32)
|
100% |
29298
38.5 IPS |
|
|
Style Transfer (F16)
|
100% |
119952
157.8 IPS |
|
|
Style Transfer (I8)
|
100% |
124193
163.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7134
254.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17333
619.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18113
646.9 IPS |
|
|
Text Classification (F32)
|
100% |
452
649.8 IPS |
|
|
Text Classification (F16)
|
100% |
654
940.6 IPS |
|
|
Text Classification (I8)
|
96% |
304
436.3 IPS |
|
|
Machine Translation (F32)
|
100% |
748
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1553
28.6 IPS |
|
|
Machine Translation (I8)
|
99% |
674
12.4 IPS |
