iPad16,3
Geekbench AI Score
3303
Single Precision Score
18732
Half Precision Score
21842
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | sfoskett |
| Upload Date | August 15 2024 07:19 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| 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 |
| Memory Information | |
|---|---|
| Size | 7.28 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1636
304.2 IPS |
|
|
Image Classification (HP)
|
100% |
8839
1.64 KIPS |
|
|
Image Classification (Q)
|
99% |
10103
1.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
958
15.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
6852
111.1 IPS |
|
|
Image Segmentation (Q)
|
100% |
6883
111.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
9778
11.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
107165
125.0 IPS |
|
|
Pose Estimation (Q)
|
94% |
181389
212.8 IPS |
|
|
Object Detection (SP)
|
100% |
1864
147.8 IPS |
|
|
Object Detection (HP)
|
100% |
11505
912.6 IPS |
|
|
Object Detection (Q)
|
93% |
14209
1.13 KIPS |
|
|
Face Detection (SP)
|
100% |
3021
35.9 IPS |
|
|
Face Detection (HP)
|
100% |
15920
189.2 IPS |
|
|
Face Detection (Q)
|
100% |
18748
222.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5766
44.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
62816
484.0 IPS |
|
|
Depth Estimation (Q)
|
97% |
68797
532.0 IPS |
|
|
Style Transfer (SP)
|
100% |
14942
19.2 IPS |
|
|
Style Transfer (HP)
|
100% |
159692
205.3 IPS |
|
|
Style Transfer (Q)
|
100% |
159577
205.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4926
181.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
23091
852.6 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
35300
1.31 KIPS |
|
|
Text Classification (SP)
|
100% |
1886
2.52 KIPS |
|
|
Text Classification (HP)
|
71% |
6448
9.27 KIPS |
|
|
Text Classification (Q)
|
69% |
6243
9.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
2244
38.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2996
51.6 IPS |
|
|
Machine Translation (Q)
|
98% |
3041
52.5 IPS |
