iPad16,3
Geekbench ML Score
9489
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 10 2024 08:13 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPad16,3 |
| Model ID | iPad16,3 |
| Motherboard | J717AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 9 Cores |
| Identifier | ARM |
| Base Frequency | 4.41 GHz |
| Cluster 1 | 3 Cores |
| Cluster 2 | 6 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 | 7.28 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4164
779.1 IPS |
|
|
Image Classification (F16)
|
100% |
8408
1.57 KIPS |
|
|
Image Classification (I8)
|
99% |
9089
1.70 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2049
34.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2439
40.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
2455
41.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
27082
32.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
99809
120.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
101926
123.4 IPS |
|
|
Object Detection (F32)
|
100% |
3679
274.7 IPS |
|
|
Object Detection (F16)
|
100% |
5826
434.9 IPS |
|
|
Object Detection (I8)
|
97% |
3427
255.9 IPS |
|
|
Face Detection (F32)
|
100% |
11578
137.7 IPS |
|
|
Face Detection (F16)
|
97% |
14690
174.7 IPS |
|
|
Face Detection (I8)
|
96% |
13955
165.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
19832
153.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
48934
379.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
51048
395.9 IPS |
|
|
Style Transfer (F32)
|
100% |
55043
72.4 IPS |
|
|
Style Transfer (F16)
|
100% |
154701
203.5 IPS |
|
|
Style Transfer (I8)
|
100% |
151194
198.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8834
315.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
21317
761.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
21721
775.7 IPS |
|
|
Text Classification (F32)
|
100% |
1490
2.14 KIPS |
|
|
Text Classification (F16)
|
100% |
1432
2.06 KIPS |
|
|
Text Classification (I8)
|
96% |
1068
1.54 KIPS |
|
|
Machine Translation (F32)
|
100% |
1115
20.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1831
33.7 IPS |
|
|
Machine Translation (I8)
|
99% |
912
16.8 IPS |
