LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
1777
Single Precision Score
841
Half Precision Score
3868
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | August 14 2025 04:35 PM |
| Views | 6 |
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% |
1310
243.7 IPS |
|
|
Image Classification (HP)
|
100% |
368
68.4 IPS |
|
|
Image Classification (Q)
|
99% |
2841
529.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
859
13.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
564
9.14 IPS |
|
|
Image Segmentation (Q)
|
98% |
3624
58.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2564
2.99 IPS |
|
|
Pose Estimation (HP)
|
100% |
1480
1.73 IPS |
|
|
Pose Estimation (Q)
|
94% |
8090
9.49 IPS |
|
|
Object Detection (SP)
|
100% |
1288
102.2 IPS |
|
|
Object Detection (HP)
|
100% |
427
33.8 IPS |
|
|
Object Detection (Q)
|
86% |
2852
229.2 IPS |
|
|
Face Detection (SP)
|
100% |
3021
35.9 IPS |
|
|
Face Detection (HP)
|
100% |
976
11.6 IPS |
|
|
Face Detection (Q)
|
97% |
5203
62.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
3420
26.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1161
8.94 IPS |
|
|
Depth Estimation (Q)
|
78% |
6897
55.0 IPS |
|
|
Style Transfer (SP)
|
100% |
5712
7.34 IPS |
|
|
Style Transfer (HP)
|
100% |
4053
5.21 IPS |
|
|
Style Transfer (Q)
|
98% |
10641
13.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1193
44.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
983
36.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3152
116.7 IPS |
|
|
Text Classification (SP)
|
100% |
1043
1.39 KIPS |
|
|
Text Classification (HP)
|
100% |
564
752.7 IPS |
|
|
Text Classification (Q)
|
97% |
1337
1.79 KIPS |
|
|
Machine Translation (SP)
|
100% |
1151
19.8 IPS |
|
|
Machine Translation (HP)
|
100% |
532
9.17 IPS |
|
|
Machine Translation (Q)
|
65% |
1964
39.5 IPS |
