iPad (9th generation)
Geekbench ML Score
1652
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 04:16 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPad (9th generation) |
| Model ID | iPad12,1 |
| Motherboard | J181AP |
| CPU Information | |
|---|---|
| Name | Apple A13 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.66 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 96.0 KB x 1 |
| L1 Data Cache | 48.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 2.87 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
285
53.4 IPS |
|
|
Image Classification (F16)
|
100% |
2579
482.7 IPS |
|
|
Image Classification (I8)
|
99% |
2615
489.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
231
3.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
334
5.57 IPS |
|
|
Image Segmentation (I8)
|
100% |
329
5.50 IPS |
|
|
Pose Estimation (F32)
|
100% |
2255
2.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
25776
31.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
25709
31.1 IPS |
|
|
Object Detection (F32)
|
100% |
515
38.4 IPS |
|
|
Object Detection (F16)
|
100% |
1127
84.1 IPS |
|
|
Object Detection (I8)
|
97% |
459
34.3 IPS |
|
|
Face Detection (F32)
|
100% |
2400
28.5 IPS |
|
|
Face Detection (F16)
|
98% |
4648
55.3 IPS |
|
|
Face Detection (I8)
|
97% |
4855
57.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2501
19.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
20830
161.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
20330
157.7 IPS |
|
|
Style Transfer (F32)
|
100% |
5916
7.78 IPS |
|
|
Style Transfer (F16)
|
100% |
17543
23.1 IPS |
|
|
Style Transfer (I8)
|
100% |
17709
23.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
991
35.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4881
174.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4858
173.5 IPS |
|
|
Text Classification (F32)
|
100% |
228
328.1 IPS |
|
|
Text Classification (F16)
|
100% |
300
430.6 IPS |
|
|
Text Classification (I8)
|
96% |
296
424.8 IPS |
|
|
Machine Translation (F32)
|
100% |
146
2.68 IPS |
|
|
Machine Translation (F16)
|
100% |
172
3.17 IPS |
|
|
Machine Translation (I8)
|
99% |
144
2.65 IPS |
