LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
1748
Single Precision Score
838
Half Precision Score
3682
Quantized Score
Geekbench AI 1.7.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | March 29 2026 09:05 AM |
| Views | 10 |
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% |
1303
242.2 IPS |
|
|
Image Classification (HP)
|
100% |
375
69.8 IPS |
|
|
Image Classification (Q)
|
99% |
2795
521.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
824
13.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
590
9.57 IPS |
|
|
Image Segmentation (Q)
|
98% |
3403
55.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2517
2.94 IPS |
|
|
Pose Estimation (HP)
|
100% |
1467
1.71 IPS |
|
|
Pose Estimation (Q)
|
94% |
7736
9.07 IPS |
|
|
Object Detection (SP)
|
100% |
1260
100.0 IPS |
|
|
Object Detection (HP)
|
100% |
437
34.7 IPS |
|
|
Object Detection (Q)
|
86% |
2709
217.7 IPS |
|
|
Face Detection (SP)
|
100% |
3037
36.1 IPS |
|
|
Face Detection (HP)
|
100% |
962
11.4 IPS |
|
|
Face Detection (Q)
|
97% |
4867
58.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
3318
25.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
1205
9.28 IPS |
|
|
Depth Estimation (Q)
|
78% |
7116
56.8 IPS |
|
|
Style Transfer (SP)
|
100% |
5572
7.16 IPS |
|
|
Style Transfer (HP)
|
100% |
4042
5.20 IPS |
|
|
Style Transfer (Q)
|
98% |
10494
13.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1238
45.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
986
36.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2691
99.6 IPS |
|
|
Text Classification (SP)
|
100% |
963
1.29 KIPS |
|
|
Text Classification (HP)
|
100% |
487
649.4 IPS |
|
|
Text Classification (Q)
|
97% |
1180
1.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
1175
20.2 IPS |
|
|
Machine Translation (HP)
|
100% |
538
9.26 IPS |
|
|
Machine Translation (Q)
|
65% |
1993
40.1 IPS |
