LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
1750
Single Precision Score
854
Half Precision Score
3846
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | August 14 2025 04:44 PM |
| Views | 7 |
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% |
1306
242.9 IPS |
|
|
Image Classification (HP)
|
100% |
368
68.4 IPS |
|
|
Image Classification (Q)
|
99% |
2820
526.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
857
13.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
585
9.48 IPS |
|
|
Image Segmentation (Q)
|
98% |
3734
60.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2540
2.96 IPS |
|
|
Pose Estimation (HP)
|
100% |
1494
1.74 IPS |
|
|
Pose Estimation (Q)
|
94% |
7986
9.36 IPS |
|
|
Object Detection (SP)
|
100% |
1272
100.9 IPS |
|
|
Object Detection (HP)
|
100% |
423
33.6 IPS |
|
|
Object Detection (Q)
|
86% |
2733
219.6 IPS |
|
|
Face Detection (SP)
|
100% |
3044
36.2 IPS |
|
|
Face Detection (HP)
|
100% |
984
11.7 IPS |
|
|
Face Detection (Q)
|
97% |
5282
63.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
3417
26.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1196
9.21 IPS |
|
|
Depth Estimation (Q)
|
78% |
7042
56.2 IPS |
|
|
Style Transfer (SP)
|
100% |
4808
6.18 IPS |
|
|
Style Transfer (HP)
|
100% |
4049
5.20 IPS |
|
|
Style Transfer (Q)
|
98% |
10954
14.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1245
46.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
993
36.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2851
105.6 IPS |
|
|
Text Classification (SP)
|
100% |
1027
1.37 KIPS |
|
|
Text Classification (HP)
|
100% |
584
778.9 IPS |
|
|
Text Classification (Q)
|
97% |
1307
1.75 KIPS |
|
|
Machine Translation (SP)
|
100% |
1169
20.1 IPS |
|
|
Machine Translation (HP)
|
100% |
549
9.45 IPS |
|
|
Machine Translation (Q)
|
65% |
2033
40.8 IPS |
