iPhone XS Max
Geekbench ML Score
1169
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 28 2024 01:56 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6 |
| 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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
197
36.9 IPS |
|
|
Image Classification (F16)
|
100% |
1955
365.9 IPS |
|
|
Image Classification (I8)
|
99% |
1969
368.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
167
2.80 IPS |
|
|
Image Segmentation (F16)
|
100% |
258
4.30 IPS |
|
|
Image Segmentation (I8)
|
100% |
256
4.28 IPS |
|
|
Pose Estimation (F32)
|
100% |
1567
1.90 IPS |
|
|
Pose Estimation (F16)
|
100% |
22245
26.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
22525
27.3 IPS |
|
|
Object Detection (F32)
|
100% |
419
31.3 IPS |
|
|
Object Detection (F16)
|
100% |
572
42.7 IPS |
|
|
Object Detection (I8)
|
97% |
462
34.5 IPS |
|
|
Face Detection (F32)
|
100% |
1787
21.3 IPS |
|
|
Face Detection (F16)
|
98% |
2212
26.3 IPS |
|
|
Face Detection (I8)
|
97% |
2235
26.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1829
14.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
17474
135.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
17568
136.2 IPS |
|
|
Style Transfer (F32)
|
100% |
4414
5.81 IPS |
|
|
Style Transfer (F16)
|
100% |
5148
6.77 IPS |
|
|
Style Transfer (I8)
|
100% |
5274
6.94 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
819
29.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3680
131.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
3564
127.3 IPS |
|
|
Text Classification (F32)
|
100% |
170
244.5 IPS |
|
|
Text Classification (F16)
|
100% |
211
302.8 IPS |
|
|
Text Classification (I8)
|
96% |
212
305.4 IPS |
|
|
Machine Translation (F32)
|
100% |
145
2.67 IPS |
|
|
Machine Translation (F16)
|
100% |
144
2.65 IPS |
|
|
Machine Translation (I8)
|
99% |
149
2.74 IPS |
