iPhone 8
Geekbench ML Score
615
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| User | Stephen_L |
| Upload Date | August 26 2024 09:43 AM |
| Views | 3 |
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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
223
41.7 IPS |
|
|
Image Classification (F16)
|
100% |
180
33.6 IPS |
|
|
Image Classification (I8)
|
99% |
190
35.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
179
2.98 IPS |
|
|
Image Segmentation (F16)
|
100% |
199
3.33 IPS |
|
|
Image Segmentation (I8)
|
100% |
196
3.27 IPS |
|
|
Pose Estimation (F32)
|
100% |
2070
2.51 IPS |
|
|
Pose Estimation (F16)
|
100% |
2620
3.17 IPS |
|
|
Pose Estimation (I8)
|
100% |
2590
3.14 IPS |
|
|
Object Detection (F32)
|
100% |
296
22.1 IPS |
|
|
Object Detection (F16)
|
100% |
299
22.3 IPS |
|
|
Object Detection (I8)
|
97% |
352
26.3 IPS |
|
|
Face Detection (F32)
|
100% |
939
11.2 IPS |
|
|
Face Detection (F16)
|
100% |
956
11.4 IPS |
|
|
Face Detection (I8)
|
99% |
940
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2638
20.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2833
22.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
2787
21.6 IPS |
|
|
Style Transfer (F32)
|
100% |
4628
6.09 IPS |
|
|
Style Transfer (F16)
|
100% |
5790
7.62 IPS |
|
|
Style Transfer (I8)
|
100% |
4995
6.57 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1051
37.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
979
35.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
987
35.3 IPS |
|
|
Text Classification (F32)
|
100% |
53
76.4 IPS |
|
|
Text Classification (F16)
|
100% |
195
279.9 IPS |
|
|
Text Classification (I8)
|
96% |
197
283.8 IPS |
|
|
Machine Translation (F32)
|
100% |
255
4.69 IPS |
|
|
Machine Translation (F16)
|
100% |
130
2.38 IPS |
|
|
Machine Translation (I8)
|
99% |
129
2.37 IPS |
