iPad17,2
Geekbench AI Score
12732
Single Precision Score
22854
Half Precision Score
22852
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | qingluoa |
| Upload Date | October 30 2025 01:55 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 26.0.1 |
| Model | iPad17,2 |
| Model ID | iPad17,2 |
| Motherboard | J818AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM |
| Base Frequency | 4.43 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 15.13 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6096
1.13 KIPS |
|
|
Image Classification (HP)
|
100% |
10176
1.89 KIPS |
|
|
Image Classification (Q)
|
97% |
9604
1.79 KIPS |
|
|
Image Segmentation (SP)
|
100% |
9956
161.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
15455
250.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
16725
271.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
37651
43.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
90993
106.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
105998
124.2 IPS |
|
|
Object Detection (SP)
|
100% |
6268
497.2 IPS |
|
|
Object Detection (HP)
|
100% |
10999
872.4 IPS |
|
|
Object Detection (Q)
|
93% |
9833
784.5 IPS |
|
|
Face Detection (SP)
|
100% |
18013
214.0 IPS |
|
|
Face Detection (HP)
|
100% |
32047
380.8 IPS |
|
|
Face Detection (Q)
|
100% |
25815
306.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
27607
212.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
50953
392.6 IPS |
|
|
Depth Estimation (Q)
|
86% |
51476
401.9 IPS |
|
|
Style Transfer (SP)
|
100% |
78568
101.0 IPS |
|
|
Style Transfer (HP)
|
100% |
165674
213.0 IPS |
|
|
Style Transfer (Q)
|
96% |
203014
262.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
15638
577.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
30821
1.14 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28830
1.06 KIPS |
|
|
Text Classification (SP)
|
100% |
2101
2.80 KIPS |
|
|
Text Classification (HP)
|
99% |
5594
7.47 KIPS |
|
|
Text Classification (Q)
|
93% |
5593
7.51 KIPS |
|
|
Machine Translation (SP)
|
100% |
6092
104.9 IPS |
|
|
Machine Translation (HP)
|
100% |
5296
91.2 IPS |
|
|
Machine Translation (Q)
|
98% |
5335
92.2 IPS |
