iPad16,1
Geekbench AI Score
2731
Single Precision Score
4602
Half Precision Score
3710
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | cellphonehater |
| Upload Date | July 05 2025 04:05 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| Model | iPad16,1 |
| Model ID | iPad16,1 |
| Motherboard | J410AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.72 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
664
123.6 IPS |
|
|
Image Classification (HP)
|
100% |
561
104.4 IPS |
|
|
Image Classification (Q)
|
96% |
433
80.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
546
8.85 IPS |
|
|
Image Segmentation (HP)
|
100% |
739
12.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
855
13.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2188
2.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
4702
5.49 IPS |
|
|
Pose Estimation (Q)
|
95% |
3981
4.67 IPS |
|
|
Object Detection (SP)
|
100% |
1290
102.3 IPS |
|
|
Object Detection (HP)
|
97% |
3344
266.2 IPS |
|
|
Object Detection (Q)
|
94% |
2355
187.7 IPS |
|
|
Face Detection (SP)
|
100% |
3247
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
6771
80.5 IPS |
|
|
Face Detection (Q)
|
100% |
3768
44.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6537
50.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
12876
99.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
8774
68.6 IPS |
|
|
Style Transfer (SP)
|
100% |
20330
26.1 IPS |
|
|
Style Transfer (HP)
|
100% |
32676
42.0 IPS |
|
|
Style Transfer (Q)
|
96% |
24416
31.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4709
173.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5737
211.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4420
163.2 IPS |
|
|
Text Classification (SP)
|
100% |
3238
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
5593
7.47 KIPS |
|
|
Text Classification (Q)
|
93% |
5603
7.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
3432
59.1 IPS |
|
|
Machine Translation (HP)
|
98% |
7159
123.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7135
123.3 IPS |
