iPad16,3
Geekbench ML Score
8820
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 07:22 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| Model | iPad16,3 |
| Model ID | iPad16,3 |
| Motherboard | J717AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 9 Cores |
| Identifier | ARM |
| Base Frequency | 4.41 GHz |
| Cluster 1 | 3 Cores |
| Cluster 2 | 6 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 | 7.28 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4261
797.3 IPS |
|
|
Image Classification (F16)
|
100% |
8296
1.55 KIPS |
|
|
Image Classification (I8)
|
99% |
8978
1.68 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1817
30.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
2297
38.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
2293
38.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
26420
32.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
100713
122.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
100131
121.3 IPS |
|
|
Object Detection (F32)
|
100% |
3118
232.8 IPS |
|
|
Object Detection (F16)
|
100% |
5710
426.3 IPS |
|
|
Object Detection (I8)
|
97% |
3218
240.3 IPS |
|
|
Face Detection (F32)
|
100% |
11181
132.9 IPS |
|
|
Face Detection (F16)
|
97% |
13608
161.8 IPS |
|
|
Face Detection (I8)
|
96% |
13486
160.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
15976
123.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
42598
330.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
42150
326.9 IPS |
|
|
Style Transfer (F32)
|
100% |
54012
71.0 IPS |
|
|
Style Transfer (F16)
|
100% |
150144
197.5 IPS |
|
|
Style Transfer (I8)
|
100% |
152814
201.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8362
298.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
20196
721.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
21142
755.0 IPS |
|
|
Text Classification (F32)
|
100% |
1354
1.95 KIPS |
|
|
Text Classification (F16)
|
100% |
1394
2.00 KIPS |
|
|
Text Classification (I8)
|
96% |
1044
1.50 KIPS |
|
|
Machine Translation (F32)
|
100% |
650
12.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1796
33.0 IPS |
|
|
Machine Translation (I8)
|
99% |
835
15.4 IPS |
