iPhone X
Geekbench ML Score
636
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 23 2024 02:43 PM |
| Views | 1 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
220
41.1 IPS |
|
|
Image Classification (F16)
|
100% |
151
28.2 IPS |
|
|
Image Classification (I8)
|
99% |
148
27.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
189
3.16 IPS |
|
|
Image Segmentation (F16)
|
100% |
202
3.37 IPS |
|
|
Image Segmentation (I8)
|
100% |
201
3.35 IPS |
|
|
Pose Estimation (F32)
|
100% |
2385
2.89 IPS |
|
|
Pose Estimation (F16)
|
100% |
2722
3.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
2803
3.39 IPS |
|
|
Object Detection (F32)
|
100% |
261
19.5 IPS |
|
|
Object Detection (F16)
|
100% |
264
19.7 IPS |
|
|
Object Detection (I8)
|
97% |
296
22.1 IPS |
|
|
Face Detection (F32)
|
100% |
978
11.6 IPS |
|
|
Face Detection (F16)
|
100% |
906
10.8 IPS |
|
|
Face Detection (I8)
|
99% |
1042
12.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
2306
17.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
2491
19.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
2522
19.6 IPS |
|
|
Style Transfer (F32)
|
100% |
4706
6.19 IPS |
|
|
Style Transfer (F16)
|
100% |
5001
6.58 IPS |
|
|
Style Transfer (I8)
|
100% |
5141
6.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1166
41.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
940
33.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1073
38.3 IPS |
|
|
Text Classification (F32)
|
100% |
51
72.7 IPS |
|
|
Text Classification (F16)
|
100% |
196
281.6 IPS |
|
|
Text Classification (I8)
|
96% |
201
288.3 IPS |
|
|
Machine Translation (F32)
|
100% |
315
5.80 IPS |
|
|
Machine Translation (F16)
|
100% |
247
4.54 IPS |
|
|
Machine Translation (I8)
|
99% |
314
5.78 IPS |
