iPad Pro (11-inch, 4th generation)
Geekbench ML Score
7551
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | neangel72 |
| Upload Date | April 26 2024 06:41 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| Model | iPad Pro (11-inch, 4th generation) |
| Model ID | iPad14,3 |
| Motherboard | J617AP |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM |
| Base Frequency | 3.49 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 7.33 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3512
657.2 IPS |
|
|
Image Classification (F16)
|
100% |
6360
1.19 KIPS |
|
|
Image Classification (I8)
|
99% |
6737
1.26 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1342
22.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1501
25.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1476
24.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
23667
28.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
79084
95.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
77892
94.3 IPS |
|
|
Object Detection (F32)
|
100% |
2798
208.9 IPS |
|
|
Object Detection (F16)
|
100% |
4756
355.1 IPS |
|
|
Object Detection (I8)
|
97% |
2589
193.3 IPS |
|
|
Face Detection (F32)
|
100% |
9254
110.0 IPS |
|
|
Face Detection (F16)
|
97% |
10935
130.0 IPS |
|
|
Face Detection (I8)
|
96% |
11062
131.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
16752
129.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
48397
375.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
49313
382.4 IPS |
|
|
Style Transfer (F32)
|
100% |
41048
54.0 IPS |
|
|
Style Transfer (F16)
|
100% |
133506
175.6 IPS |
|
|
Style Transfer (I8)
|
100% |
131761
173.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8636
308.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18859
673.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18685
667.3 IPS |
|
|
Text Classification (F32)
|
100% |
1091
1.57 KIPS |
|
|
Text Classification (F16)
|
100% |
733
1.05 KIPS |
|
|
Text Classification (I8)
|
96% |
733
1.05 KIPS |
|
|
Machine Translation (F32)
|
100% |
827
15.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2710
49.9 IPS |
|
|
Machine Translation (I8)
|
99% |
754
13.9 IPS |
