iPad Pro (11-inch, 4th generation)
Geekbench ML Score
2032
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 15 2024 04:49 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.1.1 |
| 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% |
1083
202.7 IPS |
|
|
Image Classification (F16)
|
100% |
1058
197.9 IPS |
|
|
Image Classification (I8)
|
99% |
1063
198.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
437
7.30 IPS |
|
|
Image Segmentation (F16)
|
100% |
486
8.12 IPS |
|
|
Image Segmentation (I8)
|
100% |
492
8.22 IPS |
|
|
Pose Estimation (F32)
|
100% |
5436
6.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
10201
12.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
11571
14.0 IPS |
|
|
Object Detection (F32)
|
100% |
1272
95.0 IPS |
|
|
Object Detection (F16)
|
100% |
1243
92.8 IPS |
|
|
Object Detection (I8)
|
97% |
1194
89.1 IPS |
|
|
Face Detection (F32)
|
100% |
2478
29.5 IPS |
|
|
Face Detection (F16)
|
100% |
1984
23.6 IPS |
|
|
Face Detection (I8)
|
99% |
1951
23.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
3860
29.9 IPS |
|
|
Depth Estimation (F16)
|
99% |
4234
32.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
4234
32.8 IPS |
|
|
Style Transfer (F32)
|
100% |
11365
14.9 IPS |
|
|
Style Transfer (F16)
|
100% |
13464
17.7 IPS |
|
|
Style Transfer (I8)
|
100% |
12937
17.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2868
102.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2628
93.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2566
91.6 IPS |
|
|
Text Classification (F32)
|
100% |
1061
1.53 KIPS |
|
|
Text Classification (F16)
|
100% |
735
1.06 KIPS |
|
|
Text Classification (I8)
|
96% |
737
1.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
875
16.1 IPS |
|
|
Machine Translation (F16)
|
99% |
1023
18.8 IPS |
|
|
Machine Translation (I8)
|
99% |
860
15.8 IPS |
