iPad17,1
Geekbench AI Score
13261
Single Precision Score
23308
Half Precision Score
23382
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | shafnitz |
| Upload Date | November 08 2025 03:53 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 26.2 |
| Model | iPad17,1 |
| Model ID | iPad17,1 |
| Motherboard | J817AP |
| 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 | 11.28 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6128
1.14 KIPS |
|
|
Image Classification (HP)
|
100% |
10272
1.91 KIPS |
|
|
Image Classification (Q)
|
97% |
9665
1.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
10013
162.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
15278
247.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
16754
271.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
37455
43.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
90159
105.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
106233
124.5 IPS |
|
|
Object Detection (SP)
|
100% |
6308
500.4 IPS |
|
|
Object Detection (HP)
|
100% |
10921
866.2 IPS |
|
|
Object Detection (Q)
|
93% |
9825
783.8 IPS |
|
|
Face Detection (SP)
|
100% |
18400
218.6 IPS |
|
|
Face Detection (HP)
|
100% |
32351
384.4 IPS |
|
|
Face Detection (Q)
|
100% |
26149
310.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
27681
213.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
50761
391.1 IPS |
|
|
Depth Estimation (Q)
|
86% |
51829
404.7 IPS |
|
|
Style Transfer (SP)
|
100% |
78618
101.1 IPS |
|
|
Style Transfer (HP)
|
100% |
164543
211.5 IPS |
|
|
Style Transfer (Q)
|
96% |
200891
259.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
15516
572.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
30778
1.14 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28384
1.05 KIPS |
|
|
Text Classification (SP)
|
100% |
3032
4.05 KIPS |
|
|
Text Classification (HP)
|
99% |
5501
7.34 KIPS |
|
|
Text Classification (Q)
|
93% |
5550
7.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
6159
106.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6695
115.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6741
116.5 IPS |
