Dell Inc. OptiPlex 3000 Thin Client
Geekbench AI Score
15
Single Precision Score
15
Half Precision Score
11
Quantized Score
Geekbench AI 1.5.0 for Linux x86 (64-bit)
Result Information
| User | pingwinator |
| Upload Date | October 17 2025 06:34 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Pentium Silver N6005 |
| System Information | |
|---|---|
| Operating System | Ubuntu 24.04.3 LTS |
| Model | Dell Inc. OptiPlex 3000 Thin Client |
| Motherboard | Dell Inc. 0NGT4D |
| CPU Information | |
|---|---|
| Name | Intel Pentium Silver N6005 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 156 Stepping 0 |
| Base Frequency | 3.30 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.43 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
10
1.92 IPS |
|
|
Image Classification (HP)
|
100% |
9
1.66 IPS |
|
|
Image Classification (Q)
|
97% |
7
1.27 IPS |
|
|
Image Segmentation (SP)
|
100% |
12
0.19 IPS |
|
|
Image Segmentation (HP)
|
100% |
12
0.19 IPS |
|
|
Image Segmentation (Q)
|
98% |
9
0.15 IPS |
|
|
Pose Estimation (SP)
|
100% |
14
0.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
14
0.02 IPS |
|
|
Pose Estimation (Q)
|
96% |
11
0.01 IPS |
|
|
Object Detection (SP)
|
100% |
8
0.67 IPS |
|
|
Object Detection (HP)
|
100% |
8
0.67 IPS |
|
|
Object Detection (Q)
|
87% |
7
0.52 IPS |
|
|
Face Detection (SP)
|
100% |
29
0.34 IPS |
|
|
Face Detection (HP)
|
100% |
29
0.34 IPS |
|
|
Face Detection (Q)
|
97% |
22
0.26 IPS |
|
|
Depth Estimation (SP)
|
100% |
20
0.16 IPS |
|
|
Depth Estimation (HP)
|
99% |
20
0.16 IPS |
|
|
Depth Estimation (Q)
|
64% |
13
0.12 IPS |
|
|
Style Transfer (SP)
|
100% |
43
0.05 IPS |
|
|
Style Transfer (HP)
|
100% |
43
0.05 IPS |
|
|
Style Transfer (Q)
|
98% |
33
0.04 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9
0.33 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
9
0.33 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
7
0.26 IPS |
|
|
Text Classification (SP)
|
100% |
12
15.9 IPS |
|
|
Text Classification (HP)
|
100% |
12
15.8 IPS |
|
|
Text Classification (Q)
|
91% |
9
11.7 IPS |
|
|
Machine Translation (SP)
|
100% |
22
0.38 IPS |
|
|
Machine Translation (HP)
|
100% |
22
0.38 IPS |
|
|
Machine Translation (Q)
|
58% |
12
0.28 IPS |
