iPad17,2
Geekbench AI Score
13493
Single Precision Score
24081
Half Precision Score
25400
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| User | foolsmac |
| Upload Date | January 30 2026 03:44 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| Model | iPad17,2 |
| Model ID | iPad17,2 |
| Motherboard | J818AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 9 Cores |
| Identifier | ARM |
| Base Frequency | 4.43 GHz |
| Cluster 1 | 3 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 11.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6005
1.12 KIPS |
|
|
Image Classification (HP)
|
100% |
10291
1.91 KIPS |
|
|
Image Classification (Q)
|
99% |
10415
1.94 KIPS |
|
|
Image Segmentation (SP)
|
100% |
9969
161.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
15338
248.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
16511
267.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
37202
43.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
89441
104.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
117556
137.8 IPS |
|
|
Object Detection (SP)
|
100% |
6356
504.2 IPS |
|
|
Object Detection (HP)
|
100% |
11204
888.7 IPS |
|
|
Object Detection (Q)
|
94% |
11591
924.2 IPS |
|
|
Face Detection (SP)
|
100% |
19176
227.9 IPS |
|
|
Face Detection (HP)
|
100% |
34971
415.5 IPS |
|
|
Face Detection (Q)
|
100% |
33695
400.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
27627
212.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
52010
400.7 IPS |
|
|
Depth Estimation (Q)
|
86% |
55659
434.5 IPS |
|
|
Style Transfer (SP)
|
100% |
78516
100.9 IPS |
|
|
Style Transfer (HP)
|
100% |
162430
208.8 IPS |
|
|
Style Transfer (Q)
|
96% |
207070
267.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
15373
567.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29525
1.09 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28376
1.05 KIPS |
|
|
Text Classification (SP)
|
100% |
3196
4.27 KIPS |
|
|
Text Classification (HP)
|
99% |
5625
7.51 KIPS |
|
|
Text Classification (Q)
|
93% |
5665
7.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
6917
119.1 IPS |
|
|
Machine Translation (HP)
|
100% |
8452
145.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7644
132.1 IPS |
