LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
1746
Single Precision Score
854
Half Precision Score
3712
Quantized Score
Geekbench AI 1.7.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | March 29 2026 08:29 AM |
| Views | 9 |
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% |
1286
239.1 IPS |
|
|
Image Classification (HP)
|
100% |
369
68.6 IPS |
|
|
Image Classification (Q)
|
99% |
2775
517.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
817
13.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
607
9.83 IPS |
|
|
Image Segmentation (Q)
|
98% |
3485
56.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2537
2.96 IPS |
|
|
Pose Estimation (HP)
|
100% |
1477
1.72 IPS |
|
|
Pose Estimation (Q)
|
94% |
7882
9.24 IPS |
|
|
Object Detection (SP)
|
100% |
1273
101.0 IPS |
|
|
Object Detection (HP)
|
100% |
434
34.4 IPS |
|
|
Object Detection (Q)
|
86% |
2675
215.0 IPS |
|
|
Face Detection (SP)
|
100% |
3106
36.9 IPS |
|
|
Face Detection (HP)
|
100% |
1006
12.0 IPS |
|
|
Face Detection (Q)
|
97% |
4925
58.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
3281
25.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1232
9.49 IPS |
|
|
Depth Estimation (Q)
|
78% |
6986
55.7 IPS |
|
|
Style Transfer (SP)
|
100% |
5582
7.18 IPS |
|
|
Style Transfer (HP)
|
100% |
4095
5.26 IPS |
|
|
Style Transfer (Q)
|
98% |
10481
13.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1247
46.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
996
36.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2894
107.2 IPS |
|
|
Text Classification (SP)
|
100% |
996
1.33 KIPS |
|
|
Text Classification (HP)
|
100% |
534
712.3 IPS |
|
|
Text Classification (Q)
|
97% |
1183
1.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
1100
18.9 IPS |
|
|
Machine Translation (HP)
|
100% |
534
9.21 IPS |
|
|
Machine Translation (Q)
|
65% |
1977
39.7 IPS |
