LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
1780
Single Precision Score
869
Half Precision Score
3931
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | August 14 2025 04:40 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i3-1315U |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | ECS RPLU-MINI |
| Motherboard | ECS RPLU-MINI |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i3-1315U |
| Topology | 1 Processor, 6 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 3 |
| Base Frequency | 1.20 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1302
242.2 IPS |
|
|
Image Classification (HP)
|
100% |
382
71.1 IPS |
|
|
Image Classification (Q)
|
99% |
2808
523.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
859
13.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
611
9.91 IPS |
|
|
Image Segmentation (Q)
|
98% |
3698
60.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2546
2.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
1490
1.74 IPS |
|
|
Pose Estimation (Q)
|
94% |
8133
9.54 IPS |
|
|
Object Detection (SP)
|
100% |
1240
98.3 IPS |
|
|
Object Detection (HP)
|
100% |
444
35.2 IPS |
|
|
Object Detection (Q)
|
86% |
2745
220.6 IPS |
|
|
Face Detection (SP)
|
100% |
3071
36.5 IPS |
|
|
Face Detection (HP)
|
100% |
1011
12.0 IPS |
|
|
Face Detection (Q)
|
97% |
5053
60.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
3395
26.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
1227
9.45 IPS |
|
|
Depth Estimation (Q)
|
78% |
7294
58.2 IPS |
|
|
Style Transfer (SP)
|
100% |
5703
7.33 IPS |
|
|
Style Transfer (HP)
|
100% |
4149
5.33 IPS |
|
|
Style Transfer (Q)
|
98% |
11397
14.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1226
45.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
995
36.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3228
119.5 IPS |
|
|
Text Classification (SP)
|
100% |
1076
1.44 KIPS |
|
|
Text Classification (HP)
|
100% |
572
763.9 IPS |
|
|
Text Classification (Q)
|
97% |
1348
1.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
1154
19.9 IPS |
|
|
Machine Translation (HP)
|
100% |
543
9.35 IPS |
|
|
Machine Translation (Q)
|
65% |
2083
41.9 IPS |
