iPad Pro (11-inch 3rd generation)
Geekbench ML Score
3532
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 19 2024 06:00 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| Model | iPad Pro (11-inch 3rd generation) |
| Model ID | iPad13,4 |
| Motherboard | J517AP |
| CPU Information | |
|---|---|
| Name | Apple M1 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM |
| Base Frequency | 3.19 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 | 7.37 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1375
257.3 IPS |
|
|
Image Classification (F16)
|
100% |
2143
401.1 IPS |
|
|
Image Classification (I8)
|
99% |
2139
400.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
692
11.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
788
13.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
813
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
6295
7.62 IPS |
|
|
Pose Estimation (F16)
|
100% |
13381
16.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
13385
16.2 IPS |
|
|
Object Detection (F32)
|
100% |
1347
100.6 IPS |
|
|
Object Detection (F16)
|
100% |
1992
148.7 IPS |
|
|
Object Detection (I8)
|
97% |
1350
100.8 IPS |
|
|
Face Detection (F32)
|
100% |
3011
35.8 IPS |
|
|
Face Detection (F16)
|
97% |
5438
64.7 IPS |
|
|
Face Detection (I8)
|
97% |
5436
64.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
5742
44.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
11041
85.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
11029
85.5 IPS |
|
|
Style Transfer (F32)
|
100% |
16806
22.1 IPS |
|
|
Style Transfer (F16)
|
100% |
25789
33.9 IPS |
|
|
Style Transfer (I8)
|
100% |
26030
34.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3891
139.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4666
166.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4641
165.8 IPS |
|
|
Text Classification (F32)
|
100% |
2067
2.97 KIPS |
|
|
Text Classification (F16)
|
100% |
3401
4.89 KIPS |
|
|
Text Classification (I8)
|
96% |
3386
4.87 KIPS |
|
|
Machine Translation (F32)
|
100% |
1115
20.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1385
25.5 IPS |
|
|
Machine Translation (I8)
|
99% |
1116
20.5 IPS |
