iPhone 8
Geekbench ML Score
623
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 24 2024 11:51 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% |
187
35.0 IPS |
|
|
Image Classification (F16)
|
100% |
142
26.5 IPS |
|
|
Image Classification (I8)
|
99% |
146
27.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
197
3.30 IPS |
|
|
Image Segmentation (I8)
|
100% |
199
3.33 IPS |
|
|
Pose Estimation (F32)
|
100% |
2221
2.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
2681
3.25 IPS |
|
|
Pose Estimation (I8)
|
100% |
2546
3.08 IPS |
|
|
Object Detection (F32)
|
100% |
276
20.6 IPS |
|
|
Object Detection (F16)
|
100% |
282
21.1 IPS |
|
|
Object Detection (I8)
|
97% |
260
19.4 IPS |
|
|
Face Detection (F32)
|
100% |
979
11.6 IPS |
|
|
Face Detection (F16)
|
100% |
1027
12.2 IPS |
|
|
Face Detection (I8)
|
99% |
939
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2178
16.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
2380
18.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
2454
19.0 IPS |
|
|
Style Transfer (F32)
|
100% |
4414
5.81 IPS |
|
|
Style Transfer (F16)
|
100% |
4853
6.38 IPS |
|
|
Style Transfer (I8)
|
100% |
4639
6.10 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1175
42.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
998
35.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1201
42.9 IPS |
|
|
Text Classification (F32)
|
100% |
49
70.6 IPS |
|
|
Text Classification (F16)
|
100% |
202
290.7 IPS |
|
|
Text Classification (I8)
|
96% |
198
284.2 IPS |
|
|
Machine Translation (F32)
|
100% |
315
5.80 IPS |
|
|
Machine Translation (F16)
|
100% |
242
4.45 IPS |
|
|
Machine Translation (I8)
|
99% |
315
5.80 IPS |
