iPad Pro (11-inch, 4th generation)
Geekbench ML Score
7354
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | gnu08 |
| Upload Date | May 08 2024 01:50 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
3389
634.1 IPS |
|
|
Image Classification (F16)
|
100% |
6396
1.20 KIPS |
|
|
Image Classification (I8)
|
99% |
7013
1.31 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1434
23.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1583
26.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1601
26.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
23493
28.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
81639
98.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
83514
101.1 IPS |
|
|
Object Detection (F32)
|
100% |
2864
213.8 IPS |
|
|
Object Detection (F16)
|
100% |
3693
275.7 IPS |
|
|
Object Detection (I8)
|
97% |
2616
195.3 IPS |
|
|
Face Detection (F32)
|
100% |
9294
110.5 IPS |
|
|
Face Detection (F16)
|
97% |
10655
126.7 IPS |
|
|
Face Detection (I8)
|
96% |
10705
127.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
16404
127.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
37045
287.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
35379
274.4 IPS |
|
|
Style Transfer (F32)
|
100% |
38654
50.8 IPS |
|
|
Style Transfer (F16)
|
100% |
132324
174.1 IPS |
|
|
Style Transfer (I8)
|
100% |
122095
160.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9479
338.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18383
656.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17291
617.5 IPS |
|
|
Text Classification (F32)
|
100% |
1102
1.58 KIPS |
|
|
Text Classification (F16)
|
100% |
741
1.06 KIPS |
|
|
Text Classification (I8)
|
96% |
737
1.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
795
14.6 IPS |
|
|
Machine Translation (F16)
|
100% |
2604
47.9 IPS |
|
|
Machine Translation (I8)
|
99% |
758
13.9 IPS |
