iPad16,1
Geekbench AI Score
4009
Single Precision Score
6985
Half Precision Score
5714
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | ponytoilet |
| Upload Date | June 05 2025 08:35 AM |
| Views | 6 |
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 | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1733
322.4 IPS |
|
|
Image Classification (HP)
|
100% |
2967
551.7 IPS |
|
|
Image Classification (Q)
|
96% |
2027
378.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1646
26.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2407
39.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
3076
49.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7970
9.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
16082
18.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
14042
16.5 IPS |
|
|
Object Detection (SP)
|
100% |
1803
143.0 IPS |
|
|
Object Detection (HP)
|
97% |
3351
266.8 IPS |
|
|
Object Detection (Q)
|
94% |
2376
189.4 IPS |
|
|
Face Detection (SP)
|
100% |
3333
39.6 IPS |
|
|
Face Detection (HP)
|
100% |
6935
82.4 IPS |
|
|
Face Detection (Q)
|
100% |
3882
46.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6842
52.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
12830
99.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
8995
70.3 IPS |
|
|
Style Transfer (SP)
|
100% |
21199
27.3 IPS |
|
|
Style Transfer (HP)
|
100% |
34075
43.8 IPS |
|
|
Style Transfer (Q)
|
96% |
28096
36.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4823
178.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5870
216.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4467
164.9 IPS |
|
|
Text Classification (SP)
|
100% |
3245
4.33 KIPS |
|
|
Text Classification (HP)
|
100% |
5638
7.53 KIPS |
|
|
Text Classification (Q)
|
93% |
5648
7.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
3463
59.7 IPS |
|
|
Machine Translation (HP)
|
98% |
7167
123.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7210
124.6 IPS |
