iPhone 8
Geekbench ML Score
626
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 08 2024 08:25 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.10 |
| Model | iPhone 8 |
| Model ID | iPhone10,1 |
| Motherboard | D20AP |
| 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 | 1.93 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
183
34.2 IPS |
|
|
Image Classification (F16)
|
100% |
143
26.8 IPS |
|
|
Image Classification (I8)
|
99% |
143
26.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
202
3.37 IPS |
|
|
Image Segmentation (I8)
|
100% |
202
3.38 IPS |
|
|
Pose Estimation (F32)
|
100% |
2207
2.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
2490
3.02 IPS |
|
|
Pose Estimation (I8)
|
100% |
2630
3.19 IPS |
|
|
Object Detection (F32)
|
100% |
313
23.4 IPS |
|
|
Object Detection (F16)
|
100% |
323
24.1 IPS |
|
|
Object Detection (I8)
|
97% |
309
23.1 IPS |
|
|
Face Detection (F32)
|
100% |
1034
12.3 IPS |
|
|
Face Detection (F16)
|
100% |
943
11.2 IPS |
|
|
Face Detection (I8)
|
99% |
960
11.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
2155
16.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
2368
18.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
2554
19.8 IPS |
|
|
Style Transfer (F32)
|
100% |
4104
5.40 IPS |
|
|
Style Transfer (F16)
|
100% |
4520
5.95 IPS |
|
|
Style Transfer (I8)
|
100% |
4730
6.22 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1157
41.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1094
39.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1026
36.6 IPS |
|
|
Text Classification (F32)
|
100% |
53
75.7 IPS |
|
|
Text Classification (F16)
|
100% |
198
284.3 IPS |
|
|
Text Classification (I8)
|
96% |
201
288.4 IPS |
|
|
Machine Translation (F32)
|
100% |
308
5.67 IPS |
|
|
Machine Translation (F16)
|
100% |
236
4.35 IPS |
|
|
Machine Translation (I8)
|
99% |
288
5.29 IPS |
