iPhone 8
Geekbench ML Score
611
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 04 2024 03:02 AM |
| 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% |
177
33.1 IPS |
|
|
Image Classification (F16)
|
100% |
142
26.7 IPS |
|
|
Image Classification (I8)
|
99% |
142
26.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
187
3.12 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.33 IPS |
|
|
Image Segmentation (I8)
|
100% |
202
3.38 IPS |
|
|
Pose Estimation (F32)
|
100% |
2208
2.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
2520
3.05 IPS |
|
|
Pose Estimation (I8)
|
100% |
2566
3.11 IPS |
|
|
Object Detection (F32)
|
100% |
274
20.4 IPS |
|
|
Object Detection (F16)
|
100% |
240
17.9 IPS |
|
|
Object Detection (I8)
|
97% |
339
25.3 IPS |
|
|
Face Detection (F32)
|
100% |
998
11.9 IPS |
|
|
Face Detection (F16)
|
100% |
1024
12.2 IPS |
|
|
Face Detection (I8)
|
99% |
968
11.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2172
16.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
2400
18.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
2345
18.2 IPS |
|
|
Style Transfer (F32)
|
100% |
4101
5.39 IPS |
|
|
Style Transfer (F16)
|
100% |
4511
5.93 IPS |
|
|
Style Transfer (I8)
|
100% |
4533
5.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
940
33.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1072
38.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1047
37.4 IPS |
|
|
Text Classification (F32)
|
100% |
49
69.9 IPS |
|
|
Text Classification (F16)
|
100% |
199
285.8 IPS |
|
|
Text Classification (I8)
|
96% |
200
287.3 IPS |
|
|
Machine Translation (F32)
|
100% |
313
5.76 IPS |
|
|
Machine Translation (F16)
|
100% |
238
4.38 IPS |
|
|
Machine Translation (I8)
|
99% |
293
5.39 IPS |
