iPhone 15
Geekbench ML Score
5047
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 06 2024 07:34 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.1.1 |
| Model | iPhone 15 |
| Model ID | iPhone15,4 |
| Motherboard | D37AP |
| 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 | 5.54 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
723
135.4 IPS |
|
|
Image Classification (F16)
|
100% |
5561
1.04 KIPS |
|
|
Image Classification (I8)
|
99% |
6053
1.13 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1334
22.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1986
33.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1941
32.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
11261
13.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
78152
94.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
83734
101.4 IPS |
|
|
Object Detection (F32)
|
100% |
1255
93.7 IPS |
|
|
Object Detection (F16)
|
100% |
3703
276.4 IPS |
|
|
Object Detection (I8)
|
97% |
1343
100.2 IPS |
|
|
Face Detection (F32)
|
100% |
4972
59.1 IPS |
|
|
Face Detection (F16)
|
97% |
10719
127.4 IPS |
|
|
Face Detection (I8)
|
96% |
10656
126.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
8516
66.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
36912
286.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
38672
299.9 IPS |
|
|
Style Transfer (F32)
|
100% |
20016
26.3 IPS |
|
|
Style Transfer (F16)
|
100% |
119831
157.6 IPS |
|
|
Style Transfer (I8)
|
100% |
119742
157.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3503
125.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16953
605.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17234
615.5 IPS |
|
|
Text Classification (F32)
|
100% |
388
557.4 IPS |
|
|
Text Classification (F16)
|
100% |
380
545.6 IPS |
|
|
Text Classification (I8)
|
96% |
229
329.1 IPS |
|
|
Machine Translation (F32)
|
100% |
523
9.62 IPS |
|
|
Machine Translation (F16)
|
100% |
1127
20.7 IPS |
|
|
Machine Translation (I8)
|
99% |
532
9.80 IPS |
