LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
2080
Single Precision Score
2082
Half Precision Score
1334
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | August 14 2025 05:11 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics |
| 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% |
889
165.3 IPS |
|
|
Image Classification (HP)
|
100% |
882
164.0 IPS |
|
|
Image Classification (Q)
|
100% |
767
142.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1299
21.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1522
24.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
965
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7288
8.50 IPS |
|
|
Pose Estimation (HP)
|
100% |
8367
9.76 IPS |
|
|
Pose Estimation (Q)
|
96% |
4220
4.94 IPS |
|
|
Object Detection (SP)
|
100% |
1027
81.5 IPS |
|
|
Object Detection (HP)
|
98% |
893
71.1 IPS |
|
|
Object Detection (Q)
|
86% |
856
68.9 IPS |
|
|
Face Detection (SP)
|
100% |
1971
23.4 IPS |
|
|
Face Detection (HP)
|
100% |
2356
28.0 IPS |
|
|
Face Detection (Q)
|
97% |
1458
17.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
4134
31.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
4572
35.3 IPS |
|
|
Depth Estimation (Q)
|
77% |
2936
23.5 IPS |
|
|
Style Transfer (SP)
|
100% |
15977
20.5 IPS |
|
|
Style Transfer (HP)
|
100% |
20843
26.8 IPS |
|
|
Style Transfer (Q)
|
98% |
10460
13.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2455
90.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3150
116.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1101
40.8 IPS |
|
|
Text Classification (SP)
|
100% |
736
982.0 IPS |
|
|
Text Classification (HP)
|
100% |
310
413.7 IPS |
|
|
Text Classification (Q)
|
97% |
356
476.7 IPS |
|
|
Machine Translation (SP)
|
100% |
746
12.8 IPS |
|
|
Machine Translation (HP)
|
100% |
698
12.0 IPS |
|
|
Machine Translation (Q)
|
70% |
382
7.16 IPS |
