| User | sfoskett |
| Upload Date | September 21 2024 02:26 AM |
| Views | 14 |
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone17,1 |
| Model ID | iPhone17,1 |
| Motherboard | D93AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.49 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1986
369.3 IPS |
|
|
Image Classification (HP)
|
100% |
15178
2.82 KIPS |
|
|
Image Classification (Q)
|
97% |
20347
3.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1893
30.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
14707
238.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
18330
297.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
8332
9.72 IPS |
|
|
Pose Estimation (HP)
|
100% |
149743
174.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
292099
342.4 IPS |
|
|
Object Detection (SP)
|
100% |
2092
165.9 IPS |
|
|
Object Detection (HP)
|
100% |
16270
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22598
1.81 KIPS |
|
|
Face Detection (SP)
|
100% |
3574
42.5 IPS |
|
|
Face Detection (HP)
|
100% |
41191
489.4 IPS |
|
|
Face Detection (Q)
|
100% |
55096
654.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7595
58.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
94380
727.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
160931
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
22873
29.4 IPS |
|
|
Style Transfer (HP)
|
100% |
245530
315.6 IPS |
|
|
Style Transfer (Q)
|
96% |
300702
388.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5546
204.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50462
1.86 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84143
3.11 KIPS |
|
|
Text Classification (SP)
|
100% |
3417
4.56 KIPS |
|
|
Text Classification (HP)
|
100% |
4350
5.81 KIPS |
|
|
Text Classification (Q)
|
93% |
4346
5.83 KIPS |
|
|
Machine Translation (SP)
|
100% |
3835
66.1 IPS |
|
|
Machine Translation (HP)
|
100% |
9548
164.5 IPS |
|
|
Machine Translation (Q)
|
98% |
11486
198.5 IPS |