iPad Pro (12.9-inch 5th generation)
Geekbench ML Score
3006
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 18 2024 04:57 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPad Pro (12.9-inch 5th generation) |
| Model ID | iPad13,10 |
| Motherboard | J523AP |
| CPU Information | |
|---|---|
| Name | Apple M1 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM |
| Base Frequency | 3.19 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 | 7.31 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1296
242.6 IPS |
|
|
Image Classification (F16)
|
100% |
1676
313.7 IPS |
|
|
Image Classification (I8)
|
99% |
1678
314.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
608
10.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
596
9.95 IPS |
|
|
Image Segmentation (I8)
|
100% |
603
10.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
5650
6.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
12946
15.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
12924
15.7 IPS |
|
|
Object Detection (F32)
|
100% |
1298
96.9 IPS |
|
|
Object Detection (F16)
|
100% |
1740
129.9 IPS |
|
|
Object Detection (I8)
|
97% |
1275
95.2 IPS |
|
|
Face Detection (F32)
|
100% |
2388
28.4 IPS |
|
|
Face Detection (F16)
|
97% |
4034
48.0 IPS |
|
|
Face Detection (I8)
|
97% |
4038
48.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
5202
40.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
8186
63.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
8165
63.3 IPS |
|
|
Style Transfer (F32)
|
100% |
15683
20.6 IPS |
|
|
Style Transfer (F16)
|
100% |
24408
32.1 IPS |
|
|
Style Transfer (I8)
|
100% |
24432
32.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3509
125.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4489
160.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4575
163.4 IPS |
|
|
Text Classification (F32)
|
100% |
2104
3.02 KIPS |
|
|
Text Classification (F16)
|
100% |
3401
4.89 KIPS |
|
|
Text Classification (I8)
|
96% |
3378
4.86 KIPS |
|
|
Machine Translation (F32)
|
100% |
729
13.4 IPS |
|
|
Machine Translation (F16)
|
100% |
869
16.0 IPS |
|
|
Machine Translation (I8)
|
99% |
726
13.4 IPS |
