iPhone 8
Geekbench ML Score
634
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 11 2025 10:25 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% |
181
33.8 IPS |
|
|
Image Classification (F16)
|
100% |
151
28.3 IPS |
|
|
Image Classification (I8)
|
99% |
142
26.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
188
3.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
202
3.37 IPS |
|
|
Image Segmentation (I8)
|
100% |
199
3.33 IPS |
|
|
Pose Estimation (F32)
|
100% |
2283
2.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
2659
3.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
2591
3.14 IPS |
|
|
Object Detection (F32)
|
100% |
329
24.6 IPS |
|
|
Object Detection (F16)
|
100% |
323
24.1 IPS |
|
|
Object Detection (I8)
|
97% |
300
22.4 IPS |
|
|
Face Detection (F32)
|
100% |
1010
12.0 IPS |
|
|
Face Detection (F16)
|
100% |
919
10.9 IPS |
|
|
Face Detection (I8)
|
99% |
1002
11.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2193
17.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
2365
18.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
2407
18.7 IPS |
|
|
Style Transfer (F32)
|
100% |
4573
6.01 IPS |
|
|
Style Transfer (F16)
|
100% |
5002
6.58 IPS |
|
|
Style Transfer (I8)
|
100% |
4817
6.34 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1108
39.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1029
36.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1122
40.1 IPS |
|
|
Text Classification (F32)
|
100% |
52
74.8 IPS |
|
|
Text Classification (F16)
|
100% |
200
288.1 IPS |
|
|
Text Classification (I8)
|
96% |
198
285.2 IPS |
|
|
Machine Translation (F32)
|
100% |
314
5.79 IPS |
|
|
Machine Translation (F16)
|
100% |
242
4.45 IPS |
|
|
Machine Translation (I8)
|
99% |
314
5.77 IPS |
