iPad16,2
Geekbench AI Score
3848
Single Precision Score
6925
Half Precision Score
5682
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 09 2025 03:34 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
1604
298.3 IPS |
|
|
Image Classification (HP)
|
100% |
2940
546.7 IPS |
|
|
Image Classification (Q)
|
96% |
2040
380.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1575
25.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2324
37.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
3043
49.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
7516
8.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
16161
18.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
13777
16.1 IPS |
|
|
Object Detection (SP)
|
100% |
1674
132.8 IPS |
|
|
Object Detection (HP)
|
97% |
3288
261.7 IPS |
|
|
Object Detection (Q)
|
94% |
2361
188.2 IPS |
|
|
Face Detection (SP)
|
100% |
3201
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
6954
82.6 IPS |
|
|
Face Detection (Q)
|
100% |
3865
45.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6697
51.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
12821
99.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
8994
70.3 IPS |
|
|
Style Transfer (SP)
|
100% |
20716
26.6 IPS |
|
|
Style Transfer (HP)
|
100% |
33305
42.8 IPS |
|
|
Style Transfer (Q)
|
96% |
27606
35.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4639
171.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5607
207.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4373
161.5 IPS |
|
|
Text Classification (SP)
|
100% |
3238
4.32 KIPS |
|
|
Text Classification (HP)
|
99% |
5537
7.39 KIPS |
|
|
Text Classification (Q)
|
93% |
5426
7.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
3364
57.9 IPS |
|
|
Machine Translation (HP)
|
98% |
7587
131.1 IPS |
|
|
Machine Translation (Q)
|
98% |
7632
131.9 IPS |
