iPad Pro (11-inch, 4th generation)
Geekbench ML Score
3473
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | March 27 2024 07:31 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPad Pro (11-inch, 4th generation) |
| Model ID | iPad14,3 |
| Motherboard | J617AP |
| 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 | 7.33 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1497
280.1 IPS |
|
|
Image Classification (F16)
|
100% |
1892
354.0 IPS |
|
|
Image Classification (I8)
|
99% |
1888
353.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
791
13.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
794
13.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
795
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
5905
7.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
14003
17.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
13996
16.9 IPS |
|
|
Object Detection (F32)
|
100% |
1477
110.3 IPS |
|
|
Object Detection (F16)
|
100% |
2022
150.9 IPS |
|
|
Object Detection (I8)
|
97% |
1474
110.0 IPS |
|
|
Face Detection (F32)
|
100% |
2845
33.8 IPS |
|
|
Face Detection (F16)
|
97% |
4371
52.0 IPS |
|
|
Face Detection (I8)
|
97% |
4355
51.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
5356
41.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
8629
66.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
8670
67.2 IPS |
|
|
Style Transfer (F32)
|
100% |
16977
22.3 IPS |
|
|
Style Transfer (F16)
|
100% |
26520
34.9 IPS |
|
|
Style Transfer (I8)
|
100% |
26517
34.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3775
134.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4854
173.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4884
174.4 IPS |
|
|
Text Classification (F32)
|
100% |
2067
2.97 KIPS |
|
|
Text Classification (F16)
|
100% |
3214
4.62 KIPS |
|
|
Text Classification (I8)
|
96% |
3233
4.65 KIPS |
|
|
Machine Translation (F32)
|
100% |
1260
23.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1541
28.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1269
23.3 IPS |
