LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
2076
Single Precision Score
2084
Half Precision Score
1343
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | August 14 2025 04:51 PM |
| Views | 7 |
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% |
882
164.0 IPS |
|
|
Image Classification (HP)
|
100% |
883
164.3 IPS |
|
|
Image Classification (Q)
|
100% |
752
139.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1277
20.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1508
24.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
968
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7308
8.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
8301
9.69 IPS |
|
|
Pose Estimation (Q)
|
96% |
4229
4.95 IPS |
|
|
Object Detection (SP)
|
100% |
1034
82.1 IPS |
|
|
Object Detection (HP)
|
98% |
880
70.0 IPS |
|
|
Object Detection (Q)
|
86% |
866
69.6 IPS |
|
|
Face Detection (SP)
|
100% |
1963
23.3 IPS |
|
|
Face Detection (HP)
|
100% |
2341
27.8 IPS |
|
|
Face Detection (Q)
|
97% |
1452
17.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
4148
32.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
4557
35.2 IPS |
|
|
Depth Estimation (Q)
|
77% |
2944
23.6 IPS |
|
|
Style Transfer (SP)
|
100% |
16015
20.6 IPS |
|
|
Style Transfer (HP)
|
100% |
20846
26.8 IPS |
|
|
Style Transfer (Q)
|
98% |
10584
13.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2446
90.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3183
117.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1104
40.9 IPS |
|
|
Text Classification (SP)
|
100% |
739
986.2 IPS |
|
|
Text Classification (HP)
|
100% |
324
431.9 IPS |
|
|
Text Classification (Q)
|
97% |
368
492.3 IPS |
|
|
Machine Translation (SP)
|
100% |
743
12.8 IPS |
|
|
Machine Translation (HP)
|
100% |
694
11.9 IPS |
|
|
Machine Translation (Q)
|
70% |
392
7.34 IPS |
