iPhone 8
Geekbench ML Score
414
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 13 2024 06:10 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
236
44.2 IPS |
|
|
Image Classification (F16)
|
100% |
219
40.9 IPS |
|
|
Image Classification (I8)
|
99% |
217
40.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
203
3.39 IPS |
|
|
Image Segmentation (F16)
|
100% |
206
3.44 IPS |
|
|
Image Segmentation (I8)
|
100% |
207
3.45 IPS |
|
|
Pose Estimation (F32)
|
100% |
1065
1.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
1020
1.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
1020
1.24 IPS |
|
|
Object Detection (F32)
|
100% |
240
17.9 IPS |
|
|
Object Detection (F16)
|
100% |
229
17.1 IPS |
|
|
Object Detection (I8)
|
97% |
255
19.0 IPS |
|
|
Face Detection (F32)
|
100% |
483
5.75 IPS |
|
|
Face Detection (F16)
|
100% |
471
5.60 IPS |
|
|
Face Detection (I8)
|
99% |
472
5.61 IPS |
|
|
Depth Estimation (F32)
|
100% |
625
4.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
550
4.26 IPS |
|
|
Depth Estimation (I8)
|
99% |
528
4.10 IPS |
|
|
Style Transfer (F32)
|
100% |
1571
2.07 IPS |
|
|
Style Transfer (F16)
|
100% |
1520
2.00 IPS |
|
|
Style Transfer (I8)
|
100% |
1507
1.98 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
516
18.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
539
19.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
552
19.7 IPS |
|
|
Text Classification (F32)
|
100% |
254
364.7 IPS |
|
|
Text Classification (F16)
|
100% |
214
307.2 IPS |
|
|
Text Classification (I8)
|
96% |
219
315.4 IPS |
|
|
Machine Translation (F32)
|
100% |
275
5.07 IPS |
|
|
Machine Translation (F16)
|
100% |
213
3.92 IPS |
|
|
Machine Translation (I8)
|
99% |
290
5.33 IPS |
