iPhone XS Max
Geekbench ML Score
473
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 08 2024 03:53 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.6.1 |
| Model | iPhone XS Max |
| Model ID | iPhone11,6 |
| Motherboard | D331pAP |
| CPU Information | |
|---|---|
| Name | Apple A12 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.49 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 | 2.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.67 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
274
51.3 IPS |
|
|
Image Classification (F16)
|
100% |
247
46.2 IPS |
|
|
Image Classification (I8)
|
99% |
246
46.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
243
4.05 IPS |
|
|
Image Segmentation (F16)
|
100% |
228
3.80 IPS |
|
|
Image Segmentation (I8)
|
100% |
230
3.84 IPS |
|
|
Pose Estimation (F32)
|
100% |
845
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
855
1.04 IPS |
|
|
Pose Estimation (I8)
|
100% |
829
1.00 IPS |
|
|
Object Detection (F32)
|
100% |
299
22.3 IPS |
|
|
Object Detection (F16)
|
100% |
271
20.3 IPS |
|
|
Object Detection (I8)
|
97% |
299
22.3 IPS |
|
|
Face Detection (F32)
|
100% |
616
7.33 IPS |
|
|
Face Detection (F16)
|
100% |
583
6.93 IPS |
|
|
Face Detection (I8)
|
99% |
570
6.78 IPS |
|
|
Depth Estimation (F32)
|
100% |
667
5.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
639
4.95 IPS |
|
|
Depth Estimation (I8)
|
99% |
602
4.67 IPS |
|
|
Style Transfer (F32)
|
100% |
1563
2.06 IPS |
|
|
Style Transfer (F16)
|
100% |
1495
1.97 IPS |
|
|
Style Transfer (I8)
|
100% |
1472
1.94 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
657
23.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
657
23.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
655
23.4 IPS |
|
|
Text Classification (F32)
|
100% |
270
388.6 IPS |
|
|
Text Classification (F16)
|
100% |
326
467.9 IPS |
|
|
Text Classification (I8)
|
96% |
326
468.5 IPS |
|
|
Machine Translation (F32)
|
100% |
377
6.93 IPS |
|
|
Machine Translation (F16)
|
100% |
293
5.39 IPS |
|
|
Machine Translation (I8)
|
99% |
369
6.78 IPS |
