iPad Pro (12.9-inch 5th generation)
Geekbench ML Score
5646
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | bkr899 |
| Upload Date | August 15 2024 01:08 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| Model | iPad Pro (12.9-inch 5th generation) |
| Model ID | iPad13,8 |
| Motherboard | J522AP |
| 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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2429
454.5 IPS |
|
|
Image Classification (F16)
|
100% |
4905
917.9 IPS |
|
|
Image Classification (I8)
|
99% |
5859
1.10 KIPS |
|
|
Image Segmentation (F32)
|
100% |
835
13.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
3897
65.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
3836
64.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
16778
20.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
64231
77.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
65138
78.9 IPS |
|
|
Object Detection (F32)
|
100% |
1529
114.2 IPS |
|
|
Object Detection (F16)
|
100% |
4211
314.4 IPS |
|
|
Object Detection (I8)
|
97% |
1614
120.5 IPS |
|
|
Face Detection (F32)
|
100% |
6257
74.4 IPS |
|
|
Face Detection (F16)
|
97% |
11501
136.7 IPS |
|
|
Face Detection (I8)
|
96% |
11454
136.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
10676
82.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
41526
322.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
42655
330.8 IPS |
|
|
Style Transfer (F32)
|
100% |
26234
34.5 IPS |
|
|
Style Transfer (F16)
|
100% |
115685
152.2 IPS |
|
|
Style Transfer (I8)
|
100% |
116713
153.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6403
228.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16150
576.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17922
640.0 IPS |
|
|
Text Classification (F32)
|
100% |
1049
1.51 KIPS |
|
|
Text Classification (F16)
|
100% |
2207
3.17 KIPS |
|
|
Text Classification (I8)
|
96% |
2191
3.15 KIPS |
|
|
Machine Translation (F32)
|
100% |
616
11.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1755
32.3 IPS |
|
|
Machine Translation (I8)
|
0
|
