iPad Pro (11-inch, 4th generation)
Geekbench ML Score
2150
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 13 2024 09:55 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.3.1 |
| 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 | 7.34 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1244
232.8 IPS |
|
|
Image Classification (F16)
|
100% |
1100
205.9 IPS |
|
|
Image Classification (I8)
|
99% |
1095
204.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
560
9.35 IPS |
|
|
Image Segmentation (F16)
|
100% |
505
8.44 IPS |
|
|
Image Segmentation (I8)
|
100% |
502
8.39 IPS |
|
|
Pose Estimation (F32)
|
100% |
5776
6.99 IPS |
|
|
Pose Estimation (F16)
|
100% |
12148
14.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
12160
14.7 IPS |
|
|
Object Detection (F32)
|
100% |
1279
95.5 IPS |
|
|
Object Detection (F16)
|
100% |
1250
93.3 IPS |
|
|
Object Detection (I8)
|
97% |
1283
95.8 IPS |
|
|
Face Detection (F32)
|
100% |
2501
29.7 IPS |
|
|
Face Detection (F16)
|
100% |
2017
24.0 IPS |
|
|
Face Detection (I8)
|
99% |
2020
24.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
4144
32.1 IPS |
|
|
Depth Estimation (F16)
|
99% |
4420
34.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
4410
34.2 IPS |
|
|
Style Transfer (F32)
|
100% |
11401
15.0 IPS |
|
|
Style Transfer (F16)
|
100% |
13525
17.8 IPS |
|
|
Style Transfer (I8)
|
100% |
13576
17.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3249
116.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2892
103.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2912
104.0 IPS |
|
|
Text Classification (F32)
|
100% |
1097
1.58 KIPS |
|
|
Text Classification (F16)
|
100% |
741
1.06 KIPS |
|
|
Text Classification (I8)
|
96% |
739
1.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
926
17.0 IPS |
|
|
Machine Translation (F16)
|
99% |
1056
19.4 IPS |
|
|
Machine Translation (I8)
|
99% |
922
17.0 IPS |
