iPhone X
Geekbench ML Score
638
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | MK500 |
| Upload Date | December 02 2024 12:39 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.10 |
| Model | iPhone X |
| Model ID | iPhone10,6 |
| Motherboard | D221AP |
| CPU Information | |
|---|---|
| Name | Apple A11 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.39 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 48.0 KB x 1 |
| L1 Data Cache | 32.0 KB x 1 |
| L2 Cache | 8.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 2.76 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
176
32.9 IPS |
|
|
Image Classification (F16)
|
100% |
148
27.7 IPS |
|
|
Image Classification (I8)
|
99% |
147
27.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
187
3.12 IPS |
|
|
Image Segmentation (F16)
|
100% |
199
3.32 IPS |
|
|
Image Segmentation (I8)
|
100% |
201
3.35 IPS |
|
|
Pose Estimation (F32)
|
100% |
2314
2.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
2735
3.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
2781
3.37 IPS |
|
|
Object Detection (F32)
|
100% |
276
20.6 IPS |
|
|
Object Detection (F16)
|
100% |
280
20.9 IPS |
|
|
Object Detection (I8)
|
97% |
318
23.8 IPS |
|
|
Face Detection (F32)
|
100% |
1014
12.1 IPS |
|
|
Face Detection (F16)
|
100% |
992
11.8 IPS |
|
|
Face Detection (I8)
|
99% |
999
11.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2390
18.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2653
20.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
2804
21.7 IPS |
|
|
Style Transfer (F32)
|
100% |
4447
5.85 IPS |
|
|
Style Transfer (F16)
|
100% |
5082
6.68 IPS |
|
|
Style Transfer (I8)
|
100% |
4881
6.42 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1185
42.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1019
36.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1092
39.0 IPS |
|
|
Text Classification (F32)
|
100% |
57
82.5 IPS |
|
|
Text Classification (F16)
|
100% |
200
287.2 IPS |
|
|
Text Classification (I8)
|
96% |
198
283.8 IPS |
|
|
Machine Translation (F32)
|
100% |
274
5.05 IPS |
|
|
Machine Translation (F16)
|
100% |
234
4.30 IPS |
|
|
Machine Translation (I8)
|
99% |
304
5.60 IPS |
