iPad Pro (11-inch, 4th generation)
Geekbench ML Score
3432
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 11:48 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| 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% |
1465
274.2 IPS |
|
|
Image Classification (F16)
|
100% |
1867
349.4 IPS |
|
|
Image Classification (I8)
|
99% |
1865
349.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
798
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
778
13.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
810
13.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
5928
7.18 IPS |
|
|
Pose Estimation (F16)
|
100% |
14028
17.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
14011
17.0 IPS |
|
|
Object Detection (F32)
|
100% |
1470
109.7 IPS |
|
|
Object Detection (F16)
|
100% |
1983
148.0 IPS |
|
|
Object Detection (I8)
|
97% |
1475
110.1 IPS |
|
|
Face Detection (F32)
|
100% |
2830
33.7 IPS |
|
|
Face Detection (F16)
|
97% |
4348
51.7 IPS |
|
|
Face Detection (I8)
|
97% |
4336
51.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
5355
41.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
8631
66.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
8635
67.0 IPS |
|
|
Style Transfer (F32)
|
100% |
17035
22.4 IPS |
|
|
Style Transfer (F16)
|
100% |
26538
34.9 IPS |
|
|
Style Transfer (I8)
|
100% |
26335
34.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3738
133.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4878
174.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4862
173.6 IPS |
|
|
Text Classification (F32)
|
100% |
2045
2.94 KIPS |
|
|
Text Classification (F16)
|
100% |
2826
4.06 KIPS |
|
|
Text Classification (I8)
|
96% |
2844
4.09 KIPS |
|
|
Machine Translation (F32)
|
100% |
1264
23.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1533
28.2 IPS |
|
|
Machine Translation (I8)
|
99% |
1272
23.4 IPS |
