iPad16,1
Geekbench AI Score
4003
Single Precision Score
6885
Half Precision Score
5617
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | foolsmac |
| Upload Date | October 30 2024 09:54 PM |
| Views | 22 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| Model | iPad16,1 |
| Model ID | iPad16,1 |
| Motherboard | J410AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.76 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.73 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1750
325.4 IPS |
|
|
Image Classification (HP)
|
100% |
2941
547.0 IPS |
|
|
Image Classification (Q)
|
96% |
2030
379.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1667
27.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2425
39.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
3107
50.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7889
9.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
16033
18.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
13947
16.3 IPS |
|
|
Object Detection (SP)
|
100% |
1779
141.1 IPS |
|
|
Object Detection (HP)
|
97% |
3350
266.7 IPS |
|
|
Object Detection (Q)
|
94% |
2340
186.5 IPS |
|
|
Face Detection (SP)
|
100% |
3377
40.1 IPS |
|
|
Face Detection (HP)
|
100% |
6992
83.1 IPS |
|
|
Face Detection (Q)
|
100% |
3940
46.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7022
54.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
13612
105.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
9242
72.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21113
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
32504
41.8 IPS |
|
|
Style Transfer (Q)
|
96% |
27362
35.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4886
180.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5900
217.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4434
163.7 IPS |
|
|
Text Classification (SP)
|
100% |
3203
4.28 KIPS |
|
|
Text Classification (HP)
|
100% |
5548
7.40 KIPS |
|
|
Text Classification (Q)
|
93% |
5590
7.50 KIPS |
|
|
Machine Translation (SP)
|
100% |
3300
56.8 IPS |
|
|
Machine Translation (HP)
|
98% |
6175
106.7 IPS |
|
|
Machine Translation (Q)
|
98% |
6155
106.4 IPS |
