iPad17,2
Geekbench AI Score
12832
Single Precision Score
23497
Half Precision Score
24542
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | iPhil |
| Upload Date | February 12 2026 01:46 PM |
| Views | 3 |
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% |
5911
1.10 KIPS |
|
|
Image Classification (HP)
|
100% |
9999
1.86 KIPS |
|
|
Image Classification (Q)
|
99% |
10314
1.92 KIPS |
|
|
Image Segmentation (SP)
|
100% |
9690
157.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15094
244.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
15963
258.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
31189
36.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
84275
98.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
111806
131.0 IPS |
|
|
Object Detection (SP)
|
100% |
6012
476.9 IPS |
|
|
Object Detection (HP)
|
100% |
10919
866.1 IPS |
|
|
Object Detection (Q)
|
94% |
11127
887.2 IPS |
|
|
Face Detection (SP)
|
100% |
18962
225.3 IPS |
|
|
Face Detection (HP)
|
100% |
34083
405.0 IPS |
|
|
Face Detection (Q)
|
100% |
32550
386.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
25719
198.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
50296
387.5 IPS |
|
|
Depth Estimation (Q)
|
86% |
53873
420.6 IPS |
|
|
Style Transfer (SP)
|
100% |
71053
91.3 IPS |
|
|
Style Transfer (HP)
|
100% |
161632
207.8 IPS |
|
|
Style Transfer (Q)
|
96% |
194678
251.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
15270
563.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29206
1.08 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
27280
1.01 KIPS |
|
|
Text Classification (SP)
|
100% |
3162
4.22 KIPS |
|
|
Text Classification (HP)
|
99% |
5662
7.56 KIPS |
|
|
Text Classification (Q)
|
93% |
5698
7.65 KIPS |
|
|
Machine Translation (SP)
|
100% |
6741
116.1 IPS |
|
|
Machine Translation (HP)
|
100% |
8064
138.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7295
126.1 IPS |
