iPad16,3
Geekbench AI Score
8646
Single Precision Score
10588
Half Precision Score
9025
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | DFW |
| Upload Date | September 07 2024 03:46 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 |
| Memory Information | |
|---|---|
| Size | 15.15 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4489
834.8 IPS |
|
|
Image Classification (HP)
|
100% |
4875
906.7 IPS |
|
|
Image Classification (Q)
|
97% |
3709
692.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
4861
78.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
6742
109.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
7068
114.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
28039
32.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
30218
35.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
27990
32.8 IPS |
|
|
Object Detection (SP)
|
100% |
4715
374.0 IPS |
|
|
Object Detection (HP)
|
100% |
5227
414.6 IPS |
|
|
Object Detection (Q)
|
91% |
4150
331.6 IPS |
|
|
Face Detection (SP)
|
100% |
12543
149.0 IPS |
|
|
Face Detection (HP)
|
100% |
16067
190.9 IPS |
|
|
Face Detection (Q)
|
100% |
11557
137.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
20437
157.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
22272
171.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
17988
140.6 IPS |
|
|
Style Transfer (SP)
|
100% |
56024
72.0 IPS |
|
|
Style Transfer (HP)
|
100% |
67696
87.0 IPS |
|
|
Style Transfer (Q)
|
96% |
63561
82.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
11866
438.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
12710
469.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
9975
368.3 IPS |
|
|
Text Classification (SP)
|
100% |
2996
4.00 KIPS |
|
|
Text Classification (HP)
|
100% |
5322
7.10 KIPS |
|
|
Text Classification (Q)
|
93% |
5315
7.13 KIPS |
|
|
Machine Translation (SP)
|
100% |
1586
27.3 IPS |
|
|
Machine Translation (HP)
|
100% |
2083
35.9 IPS |
|
|
Machine Translation (Q)
|
98% |
1682
29.1 IPS |
