iPad Pro (11-inch, 4th generation)
Geekbench ML Score
3456
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 06:44 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4 |
| 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% |
1493
279.5 IPS |
|
|
Image Classification (F16)
|
100% |
1887
353.2 IPS |
|
|
Image Classification (I8)
|
99% |
1898
355.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
816
13.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
815
13.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
805
13.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
5869
7.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
14014
17.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
13966
16.9 IPS |
|
|
Object Detection (F32)
|
100% |
1459
108.9 IPS |
|
|
Object Detection (F16)
|
100% |
2007
149.8 IPS |
|
|
Object Detection (I8)
|
97% |
1463
109.2 IPS |
|
|
Face Detection (F32)
|
100% |
2756
32.8 IPS |
|
|
Face Detection (F16)
|
97% |
4294
51.1 IPS |
|
|
Face Detection (I8)
|
97% |
4302
51.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
5336
41.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
8533
66.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
8538
66.2 IPS |
|
|
Style Transfer (F32)
|
100% |
16959
22.3 IPS |
|
|
Style Transfer (F16)
|
100% |
26601
35.0 IPS |
|
|
Style Transfer (I8)
|
100% |
26456
34.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3767
134.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5045
180.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5034
179.8 IPS |
|
|
Text Classification (F32)
|
100% |
2068
2.97 KIPS |
|
|
Text Classification (F16)
|
100% |
3343
4.80 KIPS |
|
|
Text Classification (I8)
|
96% |
2979
4.28 KIPS |
|
|
Machine Translation (F32)
|
100% |
1134
20.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1507
27.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1293
23.8 IPS |
