LIVA Z5 ECS RPLU-MINI
Geekbench AI Score
1715
Single Precision Score
1689
Half Precision Score
4194
Quantized Score
Geekbench AI 1.4.0 for Linux AVX2
Result Information
| User | Tungsten |
| Upload Date | July 26 2025 04:49 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | 13th Gen Intel(R) Core(TM) i3-1315U |
| System Information | |
|---|---|
| Operating System | Ubuntu 24.04.2 LTS |
| Model | ECS RPLU-MINI |
| Motherboard | ECS RPLU-MINI |
| CPU Information | |
|---|---|
| Name | Intel Core i3-1315U |
| Topology | 1 Processor, 6 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 3 |
| Base Frequency | 4.50 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.14 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
992
184.6 IPS |
|
|
Image Classification (HP)
|
100% |
996
185.3 IPS |
|
|
Image Classification (Q)
|
100% |
2568
477.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1173
19.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1171
19.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
2413
39.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1957
2.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
1676
1.96 IPS |
|
|
Pose Estimation (Q)
|
96% |
6859
8.03 IPS |
|
|
Object Detection (SP)
|
100% |
963
76.3 IPS |
|
|
Object Detection (HP)
|
100% |
980
77.7 IPS |
|
|
Object Detection (Q)
|
88% |
2661
213.3 IPS |
|
|
Face Detection (SP)
|
100% |
2634
31.3 IPS |
|
|
Face Detection (HP)
|
100% |
2629
31.2 IPS |
|
|
Face Detection (Q)
|
100% |
5725
68.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2470
19.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2457
18.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
6761
52.6 IPS |
|
|
Style Transfer (SP)
|
100% |
5390
6.93 IPS |
|
|
Style Transfer (HP)
|
100% |
5388
6.93 IPS |
|
|
Style Transfer (Q)
|
98% |
18896
24.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1159
42.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1151
42.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3964
146.8 IPS |
|
|
Text Classification (SP)
|
100% |
1303
1.74 KIPS |
|
|
Text Classification (HP)
|
100% |
1307
1.74 KIPS |
|
|
Text Classification (Q)
|
92% |
2736
3.68 KIPS |
|
|
Machine Translation (SP)
|
100% |
1904
32.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1889
32.5 IPS |
|
|
Machine Translation (Q)
|
100% |
1881
32.4 IPS |
