iPad16,3
Geekbench ML Score
9406
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 02:27 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6 |
| Model | iPad16,3 |
| Model ID | iPad16,3 |
| Motherboard | J717AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 9 Cores |
| Identifier | ARM |
| Base Frequency | 4.40 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% |
4235
792.4 IPS |
|
|
Image Classification (F16)
|
100% |
8690
1.63 KIPS |
|
|
Image Classification (I8)
|
99% |
9243
1.73 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1978
33.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
2331
38.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
2342
39.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
27042
32.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
99197
120.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
101660
123.1 IPS |
|
|
Object Detection (F32)
|
100% |
3649
272.4 IPS |
|
|
Object Detection (F16)
|
100% |
5966
445.4 IPS |
|
|
Object Detection (I8)
|
97% |
3354
250.4 IPS |
|
|
Face Detection (F32)
|
100% |
11458
136.2 IPS |
|
|
Face Detection (F16)
|
97% |
14040
166.9 IPS |
|
|
Face Detection (I8)
|
96% |
13815
164.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
20226
156.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
43784
339.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
49849
386.6 IPS |
|
|
Style Transfer (F32)
|
100% |
55126
72.5 IPS |
|
|
Style Transfer (F16)
|
100% |
141669
186.4 IPS |
|
|
Style Transfer (I8)
|
100% |
155180
204.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9334
333.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
22136
790.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
22066
788.0 IPS |
|
|
Text Classification (F32)
|
100% |
1504
2.16 KIPS |
|
|
Text Classification (F16)
|
100% |
1497
2.15 KIPS |
|
|
Text Classification (I8)
|
96% |
1035
1.49 KIPS |
|
|
Machine Translation (F32)
|
100% |
1055
19.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1800
33.1 IPS |
|
|
Machine Translation (I8)
|
99% |
908
16.7 IPS |
