iPad Pro (12.9-inch, 6th generation)
Geekbench ML Score
3504
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 08:30 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4 |
| Model | iPad Pro (12.9-inch, 6th generation) |
| Model ID | iPad14,5 |
| Motherboard | J620AP |
| 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 | 7.31 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1500
280.7 IPS |
|
|
Image Classification (F16)
|
100% |
1897
355.0 IPS |
|
|
Image Classification (I8)
|
99% |
1892
354.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
808
13.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
804
13.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
801
13.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
5915
7.16 IPS |
|
|
Pose Estimation (F16)
|
100% |
14053
17.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
14074
17.0 IPS |
|
|
Object Detection (F32)
|
100% |
1498
111.8 IPS |
|
|
Object Detection (F16)
|
100% |
2029
151.5 IPS |
|
|
Object Detection (I8)
|
97% |
1493
111.5 IPS |
|
|
Face Detection (F32)
|
100% |
2851
33.9 IPS |
|
|
Face Detection (F16)
|
97% |
4404
52.4 IPS |
|
|
Face Detection (I8)
|
97% |
4408
52.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
5387
41.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
8697
67.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
8717
67.6 IPS |
|
|
Style Transfer (F32)
|
100% |
17083
22.5 IPS |
|
|
Style Transfer (F16)
|
100% |
26672
35.1 IPS |
|
|
Style Transfer (I8)
|
100% |
26558
34.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3793
135.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5013
179.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4986
178.1 IPS |
|
|
Text Classification (F32)
|
100% |
2111
3.03 KIPS |
|
|
Text Classification (F16)
|
100% |
3272
4.70 KIPS |
|
|
Text Classification (I8)
|
96% |
3237
4.65 KIPS |
|
|
Machine Translation (F32)
|
100% |
1282
23.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1549
28.5 IPS |
|
|
Machine Translation (I8)
|
99% |
1278
23.5 IPS |
