iPhone 8
Geekbench ML Score
631
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 04 2025 10:27 PM |
| Views | 6 |
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% |
179
33.4 IPS |
|
|
Image Classification (F16)
|
100% |
141
26.4 IPS |
|
|
Image Classification (I8)
|
99% |
144
26.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
186
3.10 IPS |
|
|
Image Segmentation (F16)
|
100% |
200
3.33 IPS |
|
|
Image Segmentation (I8)
|
100% |
199
3.32 IPS |
|
|
Pose Estimation (F32)
|
100% |
2322
2.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
2705
3.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
2634
3.19 IPS |
|
|
Object Detection (F32)
|
100% |
327
24.4 IPS |
|
|
Object Detection (F16)
|
100% |
331
24.7 IPS |
|
|
Object Detection (I8)
|
97% |
297
22.1 IPS |
|
|
Face Detection (F32)
|
100% |
971
11.5 IPS |
|
|
Face Detection (F16)
|
100% |
954
11.3 IPS |
|
|
Face Detection (I8)
|
99% |
910
10.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
2098
16.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2548
19.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
2563
19.9 IPS |
|
|
Style Transfer (F32)
|
100% |
4372
5.75 IPS |
|
|
Style Transfer (F16)
|
100% |
4868
6.40 IPS |
|
|
Style Transfer (I8)
|
100% |
4666
6.14 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1226
43.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1197
42.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1028
36.7 IPS |
|
|
Text Classification (F32)
|
100% |
48
69.2 IPS |
|
|
Text Classification (F16)
|
100% |
198
285.0 IPS |
|
|
Text Classification (I8)
|
96% |
200
287.3 IPS |
|
|
Machine Translation (F32)
|
100% |
315
5.79 IPS |
|
|
Machine Translation (F16)
|
100% |
238
4.38 IPS |
|
|
Machine Translation (I8)
|
99% |
294
5.42 IPS |
