iPad (9th generation)
Geekbench ML Score
1703
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 19 2024 05:32 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| 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% |
281
52.6 IPS |
|
|
Image Classification (F16)
|
100% |
2612
488.8 IPS |
|
|
Image Classification (I8)
|
99% |
2631
492.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
211
3.53 IPS |
|
|
Image Segmentation (F16)
|
100% |
330
5.50 IPS |
|
|
Image Segmentation (I8)
|
100% |
331
5.52 IPS |
|
|
Pose Estimation (F32)
|
100% |
2256
2.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
25714
31.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
25966
31.4 IPS |
|
|
Object Detection (F32)
|
100% |
494
36.9 IPS |
|
|
Object Detection (F16)
|
100% |
1083
80.9 IPS |
|
|
Object Detection (I8)
|
97% |
503
37.5 IPS |
|
|
Face Detection (F32)
|
100% |
2449
29.1 IPS |
|
|
Face Detection (F16)
|
98% |
4771
56.7 IPS |
|
|
Face Detection (I8)
|
97% |
4788
56.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2503
19.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
20082
155.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
21050
163.2 IPS |
|
|
Style Transfer (F32)
|
100% |
5893
7.75 IPS |
|
|
Style Transfer (F16)
|
100% |
17588
23.1 IPS |
|
|
Style Transfer (I8)
|
100% |
17441
22.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1122
40.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4974
177.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4969
177.5 IPS |
|
|
Text Classification (F32)
|
100% |
222
319.6 IPS |
|
|
Text Classification (F16)
|
100% |
271
389.7 IPS |
|
|
Text Classification (I8)
|
96% |
277
398.3 IPS |
|
|
Machine Translation (F32)
|
100% |
211
3.88 IPS |
|
|
Machine Translation (F16)
|
100% |
215
3.96 IPS |
|
|
Machine Translation (I8)
|
99% |
215
3.95 IPS |
