iPad16,3
Geekbench AI Score
3255
Single Precision Score
18640
Half Precision Score
21749
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | Ricochet |
| Upload Date | August 21 2024 07:54 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| Model | iPad16,3 |
| Model ID | iPad16,3 |
| Motherboard | J717AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 9 Cores |
| Identifier | ARM |
| Base Frequency | 4.41 GHz |
| Cluster 1 | 3 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 7.28 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1622
301.7 IPS |
|
|
Image Classification (HP)
|
100% |
9012
1.68 KIPS |
|
|
Image Classification (Q)
|
99% |
9748
1.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
928
15.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
6825
110.6 IPS |
|
|
Image Segmentation (Q)
|
100% |
6834
110.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
9545
11.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
107135
125.0 IPS |
|
|
Pose Estimation (Q)
|
94% |
180512
211.7 IPS |
|
|
Object Detection (SP)
|
100% |
1844
146.3 IPS |
|
|
Object Detection (HP)
|
100% |
11314
897.4 IPS |
|
|
Object Detection (Q)
|
93% |
14028
1.12 KIPS |
|
|
Face Detection (SP)
|
100% |
2955
35.1 IPS |
|
|
Face Detection (HP)
|
100% |
14911
177.2 IPS |
|
|
Face Detection (Q)
|
100% |
19493
231.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5661
43.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
61809
476.2 IPS |
|
|
Depth Estimation (Q)
|
97% |
67510
522.0 IPS |
|
|
Style Transfer (SP)
|
100% |
14892
19.1 IPS |
|
|
Style Transfer (HP)
|
100% |
158787
204.1 IPS |
|
|
Style Transfer (Q)
|
100% |
159919
205.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4829
178.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
22726
839.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
33544
1.24 KIPS |
|
|
Text Classification (SP)
|
100% |
1871
2.50 KIPS |
|
|
Text Classification (HP)
|
71% |
6813
9.80 KIPS |
|
|
Text Classification (Q)
|
69% |
6665
9.77 KIPS |
|
|
Machine Translation (SP)
|
100% |
2244
38.7 IPS |
|
|
Machine Translation (HP)
|
100% |
2998
51.6 IPS |
|
|
Machine Translation (Q)
|
98% |
2984
51.6 IPS |
