iPad Pro (11-inch, 4th generation)
Geekbench ML Score
3482
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 03:55 AM |
| Views | 1 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1496
279.9 IPS |
|
|
Image Classification (F16)
|
100% |
1904
356.2 IPS |
|
|
Image Classification (I8)
|
99% |
1908
356.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
820
13.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
793
13.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
796
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
5899
7.14 IPS |
|
|
Pose Estimation (F16)
|
100% |
13800
16.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
13822
16.7 IPS |
|
|
Object Detection (F32)
|
100% |
1473
109.9 IPS |
|
|
Object Detection (F16)
|
100% |
2021
150.9 IPS |
|
|
Object Detection (I8)
|
97% |
1479
110.5 IPS |
|
|
Face Detection (F32)
|
100% |
2846
33.8 IPS |
|
|
Face Detection (F16)
|
97% |
4371
52.0 IPS |
|
|
Face Detection (I8)
|
97% |
4365
51.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
5340
41.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
8589
66.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
8569
66.5 IPS |
|
|
Style Transfer (F32)
|
100% |
16978
22.3 IPS |
|
|
Style Transfer (F16)
|
100% |
26556
34.9 IPS |
|
|
Style Transfer (I8)
|
100% |
26484
34.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3725
133.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4945
176.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4858
173.5 IPS |
|
|
Text Classification (F32)
|
100% |
2120
3.05 KIPS |
|
|
Text Classification (F16)
|
100% |
3296
4.74 KIPS |
|
|
Text Classification (I8)
|
96% |
3303
4.75 KIPS |
|
|
Machine Translation (F32)
|
100% |
1267
23.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1543
28.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1262
23.2 IPS |
