iPad16,1
Geekbench AI Score
2155
Single Precision Score
2352
Half Precision Score
2300
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | October 18 2025 11:16 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| Model | iPad16,1 |
| Model ID | iPad16,1 |
| Motherboard | J410AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1024
190.5 IPS |
|
|
Image Classification (HP)
|
100% |
1134
210.9 IPS |
|
|
Image Classification (Q)
|
96% |
1293
241.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
3645
59.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
3870
62.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
3704
60.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
12222
14.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
14057
16.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
13638
16.0 IPS |
|
|
Object Detection (SP)
|
100% |
2222
176.2 IPS |
|
|
Object Detection (HP)
|
100% |
1466
116.3 IPS |
|
|
Object Detection (Q)
|
92% |
1358
108.4 IPS |
|
|
Face Detection (SP)
|
100% |
6693
79.5 IPS |
|
|
Face Detection (HP)
|
100% |
8228
97.8 IPS |
|
|
Face Detection (Q)
|
100% |
6352
75.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
10588
81.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
11380
87.7 IPS |
|
|
Depth Estimation (Q)
|
86% |
10173
79.5 IPS |
|
|
Style Transfer (SP)
|
100% |
26590
34.2 IPS |
|
|
Style Transfer (HP)
|
100% |
30735
39.5 IPS |
|
|
Style Transfer (Q)
|
96% |
30525
39.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3470
128.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3555
131.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4327
159.8 IPS |
|
|
Text Classification (SP)
|
100% |
3273
4.37 KIPS |
|
|
Text Classification (HP)
|
99% |
5615
7.49 KIPS |
|
|
Text Classification (Q)
|
93% |
5495
7.37 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
8.89 IPS |
|
|
Machine Translation (HP)
|
0% |
0
10.3 IPS |
|
|
Machine Translation (Q)
|
0% |
0
9.80 IPS |
