Acer Swift SFG16-72
Geekbench AI Score
2973
Single Precision Score
1144
Half Precision Score
5195
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 29 2024 03:14 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core Ultra 7 155H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Acer Swift SFG16-72 |
| Motherboard | MTL Pipefish_MTH |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 155H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2456
456.8 IPS |
|
|
Image Classification (HP)
|
100% |
465
86.4 IPS |
|
|
Image Classification (Q)
|
99% |
4846
903.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1444
23.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
827
13.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
2859
46.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
4908
5.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
3083
3.60 IPS |
|
|
Pose Estimation (Q)
|
94% |
16755
19.6 IPS |
|
|
Object Detection (SP)
|
100% |
2033
161.2 IPS |
|
|
Object Detection (HP)
|
100% |
495
39.3 IPS |
|
|
Object Detection (Q)
|
86% |
4976
399.9 IPS |
|
|
Face Detection (SP)
|
100% |
5891
70.0 IPS |
|
|
Face Detection (HP)
|
100% |
1123
13.3 IPS |
|
|
Face Detection (Q)
|
97% |
6940
82.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6115
47.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1535
11.8 IPS |
|
|
Depth Estimation (Q)
|
78% |
11103
88.6 IPS |
|
|
Style Transfer (SP)
|
100% |
11418
14.7 IPS |
|
|
Style Transfer (HP)
|
100% |
7583
9.75 IPS |
|
|
Style Transfer (Q)
|
98% |
16825
21.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2048
75.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1478
54.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3049
112.9 IPS |
|
|
Text Classification (SP)
|
100% |
1205
1.61 KIPS |
|
|
Text Classification (HP)
|
100% |
579
773.3 IPS |
|
|
Text Classification (Q)
|
97% |
1292
1.73 KIPS |
|
|
Machine Translation (SP)
|
100% |
1504
25.9 IPS |
|
|
Machine Translation (HP)
|
100% |
588
10.1 IPS |
|
|
Machine Translation (Q)
|
65% |
2430
48.8 IPS |
