iPhone 8
Geekbench ML Score
620
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 07 2024 09:56 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% |
173
32.4 IPS |
|
|
Image Classification (F16)
|
100% |
143
26.7 IPS |
|
|
Image Classification (I8)
|
99% |
143
26.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
186
3.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
198
3.30 IPS |
|
|
Image Segmentation (I8)
|
100% |
196
3.28 IPS |
|
|
Pose Estimation (F32)
|
100% |
2222
2.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
2592
3.14 IPS |
|
|
Pose Estimation (I8)
|
100% |
2518
3.05 IPS |
|
|
Object Detection (F32)
|
100% |
361
26.9 IPS |
|
|
Object Detection (F16)
|
100% |
278
20.7 IPS |
|
|
Object Detection (I8)
|
97% |
270
20.2 IPS |
|
|
Face Detection (F32)
|
100% |
925
11.0 IPS |
|
|
Face Detection (F16)
|
100% |
924
11.0 IPS |
|
|
Face Detection (I8)
|
99% |
982
11.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2208
17.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
2549
19.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
2274
17.6 IPS |
|
|
Style Transfer (F32)
|
100% |
4386
5.77 IPS |
|
|
Style Transfer (F16)
|
100% |
4974
6.54 IPS |
|
|
Style Transfer (I8)
|
100% |
4954
6.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1156
41.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1033
36.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1143
40.8 IPS |
|
|
Text Classification (F32)
|
100% |
49
69.8 IPS |
|
|
Text Classification (F16)
|
100% |
196
281.8 IPS |
|
|
Text Classification (I8)
|
96% |
197
283.1 IPS |
|
|
Machine Translation (F32)
|
100% |
316
5.81 IPS |
|
|
Machine Translation (F16)
|
100% |
226
4.15 IPS |
|
|
Machine Translation (I8)
|
99% |
279
5.14 IPS |
