LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
2058
Single Precision Score
2101
Half Precision Score
1341
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | August 14 2025 05:15 PM |
| 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% |
883
164.2 IPS |
|
|
Image Classification (HP)
|
100% |
890
165.5 IPS |
|
|
Image Classification (Q)
|
100% |
772
143.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1285
20.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1509
24.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
966
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7313
8.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
8375
9.77 IPS |
|
|
Pose Estimation (Q)
|
96% |
4222
4.95 IPS |
|
|
Object Detection (SP)
|
100% |
1040
82.5 IPS |
|
|
Object Detection (HP)
|
98% |
894
71.1 IPS |
|
|
Object Detection (Q)
|
86% |
861
69.2 IPS |
|
|
Face Detection (SP)
|
100% |
1978
23.5 IPS |
|
|
Face Detection (HP)
|
100% |
2350
27.9 IPS |
|
|
Face Detection (Q)
|
97% |
1463
17.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
4140
31.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
4562
35.3 IPS |
|
|
Depth Estimation (Q)
|
77% |
2939
23.5 IPS |
|
|
Style Transfer (SP)
|
100% |
15992
20.6 IPS |
|
|
Style Transfer (HP)
|
100% |
20860
26.8 IPS |
|
|
Style Transfer (Q)
|
98% |
10569
13.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2439
90.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3132
115.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1099
40.7 IPS |
|
|
Text Classification (SP)
|
100% |
666
888.8 IPS |
|
|
Text Classification (HP)
|
100% |
343
457.6 IPS |
|
|
Text Classification (Q)
|
97% |
366
490.0 IPS |
|
|
Machine Translation (SP)
|
100% |
743
12.8 IPS |
|
|
Machine Translation (HP)
|
100% |
695
12.0 IPS |
|
|
Machine Translation (Q)
|
70% |
381
7.15 IPS |
