iPhone 8
Geekbench ML Score
512
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 09 2025 07:42 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.11 |
| 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% |
183
34.3 IPS |
|
|
Image Classification (F16)
|
100% |
142
26.6 IPS |
|
|
Image Classification (I8)
|
99% |
143
26.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
186
3.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
198
3.31 IPS |
|
|
Image Segmentation (I8)
|
100% |
196
3.27 IPS |
|
|
Pose Estimation (F32)
|
100% |
1092
1.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
1195
1.45 IPS |
|
|
Pose Estimation (I8)
|
100% |
1169
1.42 IPS |
|
|
Object Detection (F32)
|
100% |
310
23.2 IPS |
|
|
Object Detection (F16)
|
100% |
340
25.4 IPS |
|
|
Object Detection (I8)
|
97% |
272
20.3 IPS |
|
|
Face Detection (F32)
|
100% |
912
10.8 IPS |
|
|
Face Detection (F16)
|
100% |
894
10.6 IPS |
|
|
Face Detection (I8)
|
99% |
979
11.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1807
14.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
1872
14.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
1951
15.1 IPS |
|
|
Style Transfer (F32)
|
100% |
2781
3.66 IPS |
|
|
Style Transfer (F16)
|
100% |
3342
4.40 IPS |
|
|
Style Transfer (I8)
|
100% |
3447
4.53 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
898
32.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1010
36.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1095
39.1 IPS |
|
|
Text Classification (F32)
|
100% |
48
68.4 IPS |
|
|
Text Classification (F16)
|
100% |
201
288.8 IPS |
|
|
Text Classification (I8)
|
96% |
201
289.5 IPS |
|
|
Machine Translation (F32)
|
100% |
170
3.12 IPS |
|
|
Machine Translation (F16)
|
100% |
157
2.88 IPS |
|
|
Machine Translation (I8)
|
99% |
197
3.63 IPS |
