iPad16,3
Geekbench ML Score
6777
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 16 2024 02:29 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| Model | iPad16,3 |
| Model ID | iPad16,3 |
| Motherboard | J717AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM |
| Base Frequency | 4.40 GHz |
| Cluster 1 | 4 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 | 15.13 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4227
790.9 IPS |
|
|
Image Classification (F16)
|
100% |
4471
836.6 IPS |
|
|
Image Classification (I8)
|
99% |
4083
764.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1979
33.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
2202
36.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
2179
36.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
27185
32.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
29063
35.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
28183
34.1 IPS |
|
|
Object Detection (F32)
|
100% |
3665
273.6 IPS |
|
|
Object Detection (F16)
|
100% |
3999
298.6 IPS |
|
|
Object Detection (I8)
|
97% |
3387
252.9 IPS |
|
|
Face Detection (F32)
|
100% |
11415
135.7 IPS |
|
|
Face Detection (F16)
|
98% |
14221
169.1 IPS |
|
|
Face Detection (I8)
|
97% |
13671
162.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
19825
153.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
21907
169.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
20014
155.2 IPS |
|
|
Style Transfer (F32)
|
100% |
55491
73.0 IPS |
|
|
Style Transfer (F16)
|
100% |
65353
86.0 IPS |
|
|
Style Transfer (I8)
|
100% |
64845
85.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8496
303.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8785
313.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
9286
331.6 IPS |
|
|
Text Classification (F32)
|
100% |
1493
2.15 KIPS |
|
|
Text Classification (F16)
|
100% |
1585
2.28 KIPS |
|
|
Text Classification (I8)
|
96% |
1235
1.77 KIPS |
|
|
Machine Translation (F32)
|
100% |
1096
20.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1148
21.1 IPS |
|
|
Machine Translation (I8)
|
99% |
915
16.8 IPS |
