iPhone 15 Plus
Geekbench ML Score
4974
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 29 2024 08:04 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 15 Plus |
| Model ID | iPhone15,5 |
| Motherboard | D38AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 5.50 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1061
198.6 IPS |
|
|
Image Classification (F16)
|
100% |
5347
1.00 KIPS |
|
|
Image Classification (I8)
|
99% |
5861
1.10 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1330
22.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1978
33.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1930
32.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
11452
13.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
78707
95.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
67138
81.3 IPS |
|
|
Object Detection (F32)
|
100% |
1192
89.0 IPS |
|
|
Object Detection (F16)
|
100% |
4011
299.5 IPS |
|
|
Object Detection (I8)
|
97% |
1084
80.9 IPS |
|
|
Face Detection (F32)
|
100% |
3767
44.8 IPS |
|
|
Face Detection (F16)
|
97% |
10412
123.8 IPS |
|
|
Face Detection (I8)
|
96% |
10448
124.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
8469
65.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
36243
281.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
44278
343.4 IPS |
|
|
Style Transfer (F32)
|
100% |
21453
28.2 IPS |
|
|
Style Transfer (F16)
|
100% |
121113
159.3 IPS |
|
|
Style Transfer (I8)
|
100% |
118578
156.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3490
124.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16589
592.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16256
580.6 IPS |
|
|
Text Classification (F32)
|
100% |
367
527.2 IPS |
|
|
Text Classification (F16)
|
100% |
364
523.1 IPS |
|
|
Text Classification (I8)
|
96% |
232
333.6 IPS |
|
|
Machine Translation (F32)
|
100% |
504
9.28 IPS |
|
|
Machine Translation (F16)
|
100% |
1121
20.6 IPS |
|
|
Machine Translation (I8)
|
99% |
532
9.79 IPS |
