iPad Air (5th generation)
Geekbench ML Score
1914
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | j0hnd03 |
| Upload Date | January 19 2024 07:10 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.2 |
| Model | iPad Air (5th generation) |
| Model ID | iPad13,16 |
| Motherboard | J407AP |
| 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 | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
708
132.5 IPS |
|
|
Image Classification (F16)
|
100% |
968
181.1 IPS |
|
|
Image Classification (I8)
|
99% |
967
181.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
440
7.35 IPS |
|
|
Image Segmentation (F16)
|
100% |
412
6.88 IPS |
|
|
Image Segmentation (I8)
|
100% |
412
6.89 IPS |
|
|
Pose Estimation (F32)
|
100% |
5542
6.71 IPS |
|
|
Pose Estimation (F16)
|
100% |
11101
13.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
11102
13.4 IPS |
|
|
Object Detection (F32)
|
100% |
1093
81.6 IPS |
|
|
Object Detection (F16)
|
100% |
1066
79.6 IPS |
|
|
Object Detection (I8)
|
97% |
1094
81.7 IPS |
|
|
Face Detection (F32)
|
100% |
2165
25.7 IPS |
|
|
Face Detection (F16)
|
100% |
1809
21.5 IPS |
|
|
Face Detection (I8)
|
99% |
1812
21.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
3826
29.7 IPS |
|
|
Depth Estimation (F16)
|
99% |
4094
31.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
4095
31.8 IPS |
|
|
Style Transfer (F32)
|
100% |
10533
13.9 IPS |
|
|
Style Transfer (F16)
|
100% |
12548
16.5 IPS |
|
|
Style Transfer (I8)
|
100% |
12568
16.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2901
103.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2737
97.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2744
98.0 IPS |
|
|
Text Classification (F32)
|
100% |
1170
1.68 KIPS |
|
|
Text Classification (F16)
|
100% |
759
1.09 KIPS |
|
|
Text Classification (I8)
|
96% |
761
1.09 KIPS |
|
|
Machine Translation (F32)
|
100% |
808
14.9 IPS |
|
|
Machine Translation (F16)
|
99% |
929
17.1 IPS |
|
|
Machine Translation (I8)
|
99% |
806
14.8 IPS |
