iPad16,2
Geekbench AI Score
2040
Single Precision Score
2264
Half Precision Score
2240
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 17 2025 03:21 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| Model | iPad16,2 |
| Model ID | iPad16,2 |
| Motherboard | J411AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1039
193.2 IPS |
|
|
Image Classification (HP)
|
100% |
896
166.7 IPS |
|
|
Image Classification (Q)
|
96% |
797
148.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
3560
57.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
3738
60.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3662
59.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
11909
13.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
13502
15.8 IPS |
|
|
Pose Estimation (Q)
|
96% |
13213
15.5 IPS |
|
|
Object Detection (SP)
|
100% |
1523
120.8 IPS |
|
|
Object Detection (HP)
|
100% |
1598
126.7 IPS |
|
|
Object Detection (Q)
|
92% |
2098
167.4 IPS |
|
|
Face Detection (SP)
|
100% |
5347
63.5 IPS |
|
|
Face Detection (HP)
|
100% |
6625
78.7 IPS |
|
|
Face Detection (Q)
|
100% |
6005
71.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
9941
76.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
11208
86.3 IPS |
|
|
Depth Estimation (Q)
|
86% |
10100
78.9 IPS |
|
|
Style Transfer (SP)
|
100% |
25743
33.1 IPS |
|
|
Style Transfer (HP)
|
100% |
29373
37.8 IPS |
|
|
Style Transfer (Q)
|
96% |
29181
37.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4258
157.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4229
156.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4053
149.7 IPS |
|
|
Text Classification (SP)
|
100% |
3207
4.28 KIPS |
|
|
Text Classification (HP)
|
99% |
5317
7.10 KIPS |
|
|
Text Classification (Q)
|
93% |
5496
7.38 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
9.37 IPS |
|
|
Machine Translation (HP)
|
0% |
0
9.78 IPS |
|
|
Machine Translation (Q)
|
0% |
0
9.18 IPS |
