LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
2035
Single Precision Score
2051
Half Precision Score
1309
Quantized Score
Geekbench AI 1.7.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | March 29 2026 09:14 AM |
| Views | 9 |
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% |
874
162.6 IPS |
|
|
Image Classification (HP)
|
100% |
874
162.5 IPS |
|
|
Image Classification (Q)
|
100% |
751
139.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1257
20.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1487
24.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
959
15.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6986
8.15 IPS |
|
|
Pose Estimation (HP)
|
100% |
8135
9.49 IPS |
|
|
Pose Estimation (Q)
|
96% |
4098
4.80 IPS |
|
|
Object Detection (SP)
|
100% |
1012
80.3 IPS |
|
|
Object Detection (HP)
|
98% |
879
69.9 IPS |
|
|
Object Detection (Q)
|
86% |
851
68.4 IPS |
|
|
Face Detection (SP)
|
100% |
1950
23.2 IPS |
|
|
Face Detection (HP)
|
100% |
2329
27.7 IPS |
|
|
Face Detection (Q)
|
97% |
1450
17.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
4091
31.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
4548
35.2 IPS |
|
|
Depth Estimation (Q)
|
77% |
2860
22.9 IPS |
|
|
Style Transfer (SP)
|
100% |
15835
20.4 IPS |
|
|
Style Transfer (HP)
|
100% |
20258
26.0 IPS |
|
|
Style Transfer (Q)
|
98% |
10444
13.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2448
90.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3119
115.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1089
40.3 IPS |
|
|
Text Classification (SP)
|
100% |
703
938.5 IPS |
|
|
Text Classification (HP)
|
100% |
310
414.1 IPS |
|
|
Text Classification (Q)
|
97% |
334
447.4 IPS |
|
|
Machine Translation (SP)
|
100% |
723
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
685
11.8 IPS |
|
|
Machine Translation (Q)
|
70% |
376
7.05 IPS |
