iPhone 8
Geekbench ML Score
620
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 14 2024 09:59 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
181
33.8 IPS |
|
|
Image Classification (F16)
|
100% |
148
27.7 IPS |
|
|
Image Classification (I8)
|
99% |
147
27.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.34 IPS |
|
|
Image Segmentation (I8)
|
100% |
199
3.33 IPS |
|
|
Pose Estimation (F32)
|
100% |
2224
2.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
2643
3.20 IPS |
|
|
Pose Estimation (I8)
|
100% |
2537
3.07 IPS |
|
|
Object Detection (F32)
|
100% |
280
20.9 IPS |
|
|
Object Detection (F16)
|
100% |
329
24.5 IPS |
|
|
Object Detection (I8)
|
97% |
361
27.0 IPS |
|
|
Face Detection (F32)
|
100% |
963
11.5 IPS |
|
|
Face Detection (F16)
|
100% |
987
11.7 IPS |
|
|
Face Detection (I8)
|
99% |
971
11.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2109
16.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
2395
18.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
2371
18.4 IPS |
|
|
Style Transfer (F32)
|
100% |
4431
5.83 IPS |
|
|
Style Transfer (F16)
|
100% |
4664
6.13 IPS |
|
|
Style Transfer (I8)
|
100% |
4718
6.21 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1009
36.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1043
37.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1024
36.6 IPS |
|
|
Text Classification (F32)
|
100% |
54
77.3 IPS |
|
|
Text Classification (F16)
|
100% |
197
283.2 IPS |
|
|
Text Classification (I8)
|
96% |
200
287.4 IPS |
|
|
Machine Translation (F32)
|
100% |
316
5.82 IPS |
|
|
Machine Translation (F16)
|
100% |
204
3.76 IPS |
|
|
Machine Translation (I8)
|
99% |
255
4.69 IPS |
