iPad Pro 12.9-inch (4th generation)
Geekbench ML Score
1045
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 10:25 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPad Pro 12.9-inch (4th generation) |
| Model ID | iPad8,11 |
| Motherboard | J420AP |
| CPU Information | |
|---|---|
| Name | Apple A12Z Bionic |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM |
| Base Frequency | 2.49 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 48.0 KB x 1 |
| L1 Data Cache | 32.0 KB x 1 |
| L2 Cache | 2.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 5.53 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
463
86.6 IPS |
|
|
Image Classification (F16)
|
100% |
668
125.0 IPS |
|
|
Image Classification (I8)
|
99% |
669
125.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
295
4.92 IPS |
|
|
Image Segmentation (F16)
|
100% |
353
5.90 IPS |
|
|
Image Segmentation (I8)
|
100% |
353
5.90 IPS |
|
|
Pose Estimation (F32)
|
100% |
2519
3.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
2274
2.75 IPS |
|
|
Pose Estimation (I8)
|
100% |
2289
2.77 IPS |
|
|
Object Detection (F32)
|
100% |
496
37.0 IPS |
|
|
Object Detection (F16)
|
100% |
778
58.1 IPS |
|
|
Object Detection (I8)
|
97% |
498
37.2 IPS |
|
|
Face Detection (F32)
|
100% |
1084
12.9 IPS |
|
|
Face Detection (F16)
|
97% |
1837
21.8 IPS |
|
|
Face Detection (I8)
|
96% |
1841
21.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1338
10.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
2407
18.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
2456
19.0 IPS |
|
|
Style Transfer (F32)
|
100% |
4828
6.35 IPS |
|
|
Style Transfer (F16)
|
100% |
7570
9.96 IPS |
|
|
Style Transfer (I8)
|
100% |
7583
9.98 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1229
43.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1545
55.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1538
54.9 IPS |
|
|
Text Classification (F32)
|
100% |
268
385.3 IPS |
|
|
Text Classification (F16)
|
100% |
515
740.0 IPS |
|
|
Text Classification (I8)
|
96% |
514
739.0 IPS |
|
|
Machine Translation (F32)
|
100% |
448
8.24 IPS |
|
|
Machine Translation (F16)
|
100% |
597
11.0 IPS |
|
|
Machine Translation (I8)
|
99% |
449
8.26 IPS |
