iPad Pro (12.9-inch 5th generation)
Geekbench ML Score
2888
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 03:31 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPad Pro (12.9-inch 5th generation) |
| Model ID | iPad13,10 |
| Motherboard | J523AP |
| CPU Information | |
|---|---|
| Name | Apple M1 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM |
| Base Frequency | 3.19 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% |
1294
242.2 IPS |
|
|
Image Classification (F16)
|
100% |
1664
311.5 IPS |
|
|
Image Classification (I8)
|
99% |
1664
311.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
619
10.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
599
10.00 IPS |
|
|
Image Segmentation (I8)
|
100% |
593
9.90 IPS |
|
|
Pose Estimation (F32)
|
100% |
5634
6.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
12950
15.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
12964
15.7 IPS |
|
|
Object Detection (F32)
|
100% |
1311
97.9 IPS |
|
|
Object Detection (F16)
|
100% |
1741
129.9 IPS |
|
|
Object Detection (I8)
|
97% |
1308
97.7 IPS |
|
|
Face Detection (F32)
|
100% |
2379
28.3 IPS |
|
|
Face Detection (F16)
|
97% |
4007
47.6 IPS |
|
|
Face Detection (I8)
|
97% |
4012
47.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
5174
40.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
7161
55.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
7700
59.7 IPS |
|
|
Style Transfer (F32)
|
100% |
12731
16.7 IPS |
|
|
Style Transfer (F16)
|
100% |
24365
32.0 IPS |
|
|
Style Transfer (I8)
|
100% |
22871
30.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3097
110.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4290
153.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4033
144.0 IPS |
|
|
Text Classification (F32)
|
100% |
1760
2.53 KIPS |
|
|
Text Classification (F16)
|
100% |
3363
4.83 KIPS |
|
|
Text Classification (I8)
|
96% |
2933
4.21 KIPS |
|
|
Machine Translation (F32)
|
100% |
707
13.0 IPS |
|
|
Machine Translation (F16)
|
100% |
834
15.3 IPS |
|
|
Machine Translation (I8)
|
99% |
701
12.9 IPS |
