iPad Pro (12.9-inch, 6th generation)
Geekbench ML Score
3465
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 07:32 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| Model | iPad Pro (12.9-inch, 6th generation) |
| Model ID | iPad14,5 |
| Motherboard | J620AP |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM |
| Base Frequency | 3.49 GHz |
| Cluster 1 | 4 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 | 7.31 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1499
280.5 IPS |
|
|
Image Classification (F16)
|
100% |
1885
352.7 IPS |
|
|
Image Classification (I8)
|
99% |
1888
353.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
801
13.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
792
13.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
794
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
5920
7.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
13835
16.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
14066
17.0 IPS |
|
|
Object Detection (F32)
|
100% |
1494
111.5 IPS |
|
|
Object Detection (F16)
|
100% |
2031
151.6 IPS |
|
|
Object Detection (I8)
|
97% |
1483
110.7 IPS |
|
|
Face Detection (F32)
|
100% |
2849
33.9 IPS |
|
|
Face Detection (F16)
|
97% |
4373
52.0 IPS |
|
|
Face Detection (I8)
|
97% |
4359
51.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
5315
41.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
8592
66.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
8695
67.4 IPS |
|
|
Style Transfer (F32)
|
100% |
16948
22.3 IPS |
|
|
Style Transfer (F16)
|
100% |
26558
34.9 IPS |
|
|
Style Transfer (I8)
|
100% |
26643
35.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3802
135.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4971
177.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5006
178.8 IPS |
|
|
Text Classification (F32)
|
100% |
2101
3.02 KIPS |
|
|
Text Classification (F16)
|
100% |
2963
4.26 KIPS |
|
|
Text Classification (I8)
|
96% |
2914
4.19 KIPS |
|
|
Machine Translation (F32)
|
100% |
1280
23.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1537
28.3 IPS |
|
|
Machine Translation (I8)
|
99% |
1279
23.5 IPS |
