iPad17,2
Geekbench AI Score
5220
Single Precision Score
8626
Half Precision Score
6814
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | iPhil |
| Upload Date | February 12 2026 01:43 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
2256
419.5 IPS |
|
|
Image Classification (HP)
|
100% |
3628
674.7 IPS |
|
|
Image Classification (Q)
|
96% |
2471
461.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2330
37.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
3469
56.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
3673
59.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
10154
11.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
20157
23.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
17343
20.3 IPS |
|
|
Object Detection (SP)
|
100% |
2688
213.2 IPS |
|
|
Object Detection (HP)
|
97% |
4170
331.9 IPS |
|
|
Object Detection (Q)
|
94% |
2929
233.5 IPS |
|
|
Face Detection (SP)
|
100% |
4353
51.7 IPS |
|
|
Face Detection (HP)
|
100% |
8400
99.8 IPS |
|
|
Face Detection (Q)
|
100% |
4735
56.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
9095
70.1 IPS |
|
|
Depth Estimation (HP)
|
97% |
15192
117.4 IPS |
|
|
Depth Estimation (Q)
|
86% |
10567
82.5 IPS |
|
|
Style Transfer (SP)
|
100% |
26035
33.5 IPS |
|
|
Style Transfer (HP)
|
100% |
40851
52.5 IPS |
|
|
Style Transfer (Q)
|
96% |
33720
43.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6008
221.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7501
277.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5220
192.7 IPS |
|
|
Text Classification (SP)
|
100% |
3296
4.40 KIPS |
|
|
Text Classification (HP)
|
99% |
5662
7.56 KIPS |
|
|
Text Classification (Q)
|
93% |
5577
7.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
5136
88.5 IPS |
|
|
Machine Translation (HP)
|
98% |
9748
168.4 IPS |
|
|
Machine Translation (Q)
|
98% |
9530
164.7 IPS |
