iPhone 8
Geekbench ML Score
623
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 01 2024 09:17 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% |
176
32.9 IPS |
|
|
Image Classification (F16)
|
100% |
141
26.4 IPS |
|
|
Image Classification (I8)
|
99% |
150
28.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
186
3.11 IPS |
|
|
Image Segmentation (F16)
|
100% |
199
3.32 IPS |
|
|
Image Segmentation (I8)
|
100% |
198
3.31 IPS |
|
|
Pose Estimation (F32)
|
100% |
2249
2.72 IPS |
|
|
Pose Estimation (F16)
|
100% |
2676
3.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
2567
3.11 IPS |
|
|
Object Detection (F32)
|
100% |
314
23.5 IPS |
|
|
Object Detection (F16)
|
100% |
323
24.1 IPS |
|
|
Object Detection (I8)
|
97% |
279
20.8 IPS |
|
|
Face Detection (F32)
|
100% |
952
11.3 IPS |
|
|
Face Detection (F16)
|
100% |
1081
12.9 IPS |
|
|
Face Detection (I8)
|
99% |
1014
12.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
2050
15.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
2426
18.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
2607
20.2 IPS |
|
|
Style Transfer (F32)
|
100% |
4350
5.72 IPS |
|
|
Style Transfer (F16)
|
100% |
4860
6.39 IPS |
|
|
Style Transfer (I8)
|
100% |
4768
6.27 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
967
34.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1036
37.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1006
35.9 IPS |
|
|
Text Classification (F32)
|
100% |
49
70.5 IPS |
|
|
Text Classification (F16)
|
100% |
200
287.2 IPS |
|
|
Text Classification (I8)
|
96% |
202
290.1 IPS |
|
|
Machine Translation (F32)
|
100% |
316
5.81 IPS |
|
|
Machine Translation (F16)
|
100% |
237
4.35 IPS |
|
|
Machine Translation (I8)
|
99% |
291
5.36 IPS |
