iPhone X
Geekbench ML Score
641
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | rafaexnexus |
| Upload Date | September 10 2024 11:27 PM |
| Views | 4 |
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% |
216
40.4 IPS |
|
|
Image Classification (F16)
|
100% |
168
31.5 IPS |
|
|
Image Classification (I8)
|
99% |
154
28.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
186
3.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.34 IPS |
|
|
Image Segmentation (I8)
|
100% |
200
3.34 IPS |
|
|
Pose Estimation (F32)
|
100% |
2312
2.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
2870
3.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
2776
3.36 IPS |
|
|
Object Detection (F32)
|
100% |
292
21.8 IPS |
|
|
Object Detection (F16)
|
100% |
309
23.1 IPS |
|
|
Object Detection (I8)
|
97% |
287
21.5 IPS |
|
|
Face Detection (F32)
|
100% |
936
11.1 IPS |
|
|
Face Detection (F16)
|
100% |
872
10.4 IPS |
|
|
Face Detection (I8)
|
99% |
1044
12.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
2307
17.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
2534
19.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
2457
19.1 IPS |
|
|
Style Transfer (F32)
|
100% |
4423
5.82 IPS |
|
|
Style Transfer (F16)
|
100% |
4935
6.49 IPS |
|
|
Style Transfer (I8)
|
100% |
5012
6.59 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1010
36.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1067
38.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1071
38.3 IPS |
|
|
Text Classification (F32)
|
100% |
58
83.0 IPS |
|
|
Text Classification (F16)
|
100% |
199
286.4 IPS |
|
|
Text Classification (I8)
|
96% |
203
291.8 IPS |
|
|
Machine Translation (F32)
|
100% |
301
5.53 IPS |
|
|
Machine Translation (F16)
|
100% |
239
4.39 IPS |
|
|
Machine Translation (I8)
|
99% |
314
5.77 IPS |
