iPad mini (7th generation)
Geekbench AI Score
3888
Single Precision Score
6984
Half Precision Score
5678
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| User | mattpippen |
| Upload Date | December 29 2025 03:11 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| Model | iPad mini (7th generation) |
| Model ID | iPad16,1 |
| Motherboard | J410AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| 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% |
1612
299.7 IPS |
|
|
Image Classification (HP)
|
100% |
2949
548.4 IPS |
|
|
Image Classification (Q)
|
96% |
2031
379.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1591
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2360
38.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
3059
49.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
7630
8.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
16394
19.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
13615
16.0 IPS |
|
|
Object Detection (SP)
|
100% |
1679
133.2 IPS |
|
|
Object Detection (HP)
|
97% |
3262
259.7 IPS |
|
|
Object Detection (Q)
|
94% |
2367
188.7 IPS |
|
|
Face Detection (SP)
|
100% |
3282
39.0 IPS |
|
|
Face Detection (HP)
|
100% |
6943
82.5 IPS |
|
|
Face Detection (Q)
|
100% |
3879
46.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6658
51.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
12852
99.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
9045
70.7 IPS |
|
|
Style Transfer (SP)
|
100% |
21116
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
33611
43.2 IPS |
|
|
Style Transfer (Q)
|
96% |
27403
35.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4733
174.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5668
209.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4407
162.7 IPS |
|
|
Text Classification (SP)
|
100% |
3251
4.34 KIPS |
|
|
Text Classification (HP)
|
99% |
5775
7.71 KIPS |
|
|
Text Classification (Q)
|
93% |
5540
7.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
3389
58.4 IPS |
|
|
Machine Translation (HP)
|
98% |
7560
130.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7422
128.3 IPS |
