iPhone X
Geekbench ML Score
423
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 23 2024 02:36 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.1.1 |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
236
44.1 IPS |
|
|
Image Classification (F16)
|
100% |
222
41.6 IPS |
|
|
Image Classification (I8)
|
99% |
220
41.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
206
3.43 IPS |
|
|
Image Segmentation (F16)
|
100% |
208
3.48 IPS |
|
|
Image Segmentation (I8)
|
100% |
208
3.47 IPS |
|
|
Pose Estimation (F32)
|
100% |
1016
1.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
1003
1.21 IPS |
|
|
Pose Estimation (I8)
|
100% |
987
1.20 IPS |
|
|
Object Detection (F32)
|
100% |
247
18.4 IPS |
|
|
Object Detection (F16)
|
100% |
239
17.8 IPS |
|
|
Object Detection (I8)
|
97% |
260
19.4 IPS |
|
|
Face Detection (F32)
|
100% |
481
5.72 IPS |
|
|
Face Detection (F16)
|
100% |
473
5.62 IPS |
|
|
Face Detection (I8)
|
99% |
472
5.62 IPS |
|
|
Depth Estimation (F32)
|
100% |
614
4.77 IPS |
|
|
Depth Estimation (F16)
|
100% |
561
4.35 IPS |
|
|
Depth Estimation (I8)
|
99% |
526
4.08 IPS |
|
|
Style Transfer (F32)
|
100% |
1591
2.09 IPS |
|
|
Style Transfer (F16)
|
100% |
1578
2.08 IPS |
|
|
Style Transfer (I8)
|
100% |
1581
2.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
512
18.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
552
19.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
556
19.9 IPS |
|
|
Text Classification (F32)
|
100% |
253
363.6 IPS |
|
|
Text Classification (F16)
|
100% |
214
307.4 IPS |
|
|
Text Classification (I8)
|
96% |
220
316.6 IPS |
|
|
Machine Translation (F32)
|
100% |
313
5.76 IPS |
|
|
Machine Translation (F16)
|
100% |
264
4.86 IPS |
|
|
Machine Translation (I8)
|
99% |
330
6.07 IPS |
