iPhone 8 Plus
Geekbench ML Score
361
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 08 2026 05:27 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.7.12 |
| Model | iPhone 8 Plus |
| Model ID | iPhone10,2 |
| Motherboard | D21AP |
| 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 | 2.90 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
237
44.4 IPS |
|
|
Image Classification (F16)
|
100% |
214
40.1 IPS |
|
|
Image Classification (I8)
|
99% |
215
40.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
197
3.30 IPS |
|
|
Image Segmentation (F16)
|
100% |
198
3.30 IPS |
|
|
Image Segmentation (I8)
|
100% |
196
3.28 IPS |
|
|
Pose Estimation (F32)
|
100% |
868
1.05 IPS |
|
|
Pose Estimation (F16)
|
100% |
667
0.81 IPS |
|
|
Pose Estimation (I8)
|
100% |
664
0.80 IPS |
|
|
Object Detection (F32)
|
100% |
144
10.8 IPS |
|
|
Object Detection (F16)
|
100% |
174
13.0 IPS |
|
|
Object Detection (I8)
|
97% |
190
14.2 IPS |
|
|
Face Detection (F32)
|
100% |
433
5.15 IPS |
|
|
Face Detection (F16)
|
100% |
439
5.22 IPS |
|
|
Face Detection (I8)
|
99% |
436
5.19 IPS |
|
|
Depth Estimation (F32)
|
100% |
570
4.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
428
3.32 IPS |
|
|
Depth Estimation (I8)
|
99% |
429
3.32 IPS |
|
|
Style Transfer (F32)
|
100% |
1349
1.77 IPS |
|
|
Style Transfer (F16)
|
100% |
1388
1.83 IPS |
|
|
Style Transfer (I8)
|
100% |
1391
1.83 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
425
15.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
443
15.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
507
18.1 IPS |
|
|
Text Classification (F32)
|
100% |
206
295.9 IPS |
|
|
Text Classification (F16)
|
100% |
214
308.0 IPS |
|
|
Text Classification (I8)
|
96% |
216
310.1 IPS |
|
|
Machine Translation (F32)
|
100% |
306
5.64 IPS |
|
|
Machine Translation (F16)
|
100% |
214
3.94 IPS |
|
|
Machine Translation (I8)
|
99% |
261
4.81 IPS |
