iPad Pro (12.9-inch 2nd Generation)
Geekbench ML Score
96
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 04:36 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| Model | iPad Pro (12.9-inch 2nd Generation) |
| Model ID | iPad7,1 |
| Motherboard | J120AP |
| CPU Information | |
|---|---|
| Name | Apple A10X Fusion |
| Topology | 1 Processor, 3 Cores |
| Identifier | ARM |
| Base Frequency | 2.34 GHz |
| Cluster 1 | 3 Cores |
| L1 Instruction Cache | 64.0 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 8.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.88 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
342
64.1 IPS |
|
|
Image Classification (F16)
|
100% |
14
2.61 IPS |
|
|
Image Classification (I8)
|
99% |
14
2.61 IPS |
|
|
Image Segmentation (F32)
|
100% |
221
3.69 IPS |
|
|
Image Segmentation (F16)
|
100% |
18
0.30 IPS |
|
|
Image Segmentation (I8)
|
100% |
18
0.30 IPS |
|
|
Pose Estimation (F32)
|
100% |
1617
1.96 IPS |
|
|
Pose Estimation (F16)
|
100% |
20
0.02 IPS |
|
|
Pose Estimation (I8)
|
100% |
20
0.02 IPS |
|
|
Object Detection (F32)
|
100% |
345
25.8 IPS |
|
|
Object Detection (F16)
|
100% |
14
1.07 IPS |
|
|
Object Detection (I8)
|
97% |
346
25.8 IPS |
|
|
Face Detection (F32)
|
100% |
697
8.28 IPS |
|
|
Face Detection (F16)
|
98% |
45
0.53 IPS |
|
|
Face Detection (I8)
|
97% |
45
0.53 IPS |
|
|
Depth Estimation (F32)
|
100% |
827
6.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
31
0.24 IPS |
|
|
Depth Estimation (I8)
|
99% |
31
0.24 IPS |
|
|
Style Transfer (F32)
|
100% |
2551
3.36 IPS |
|
|
Style Transfer (F16)
|
100% |
66
0.09 IPS |
|
|
Style Transfer (I8)
|
100% |
66
0.09 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
780
27.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14
0.51 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
14
0.51 IPS |
|
|
Text Classification (F32)
|
100% |
238
341.4 IPS |
|
|
Text Classification (F16)
|
100% |
204
292.5 IPS |
|
|
Text Classification (I8)
|
96% |
204
292.6 IPS |
|
|
Machine Translation (F32)
|
100% |
327
6.02 IPS |
|
|
Machine Translation (F16)
|
100% |
32
0.59 IPS |
|
|
Machine Translation (I8)
|
99% |
328
6.03 IPS |
