innotek GmbH VirtualBox
Geekbench AI Score
43
Single Precision Score
43
Half Precision Score
32
Quantized Score
Geekbench AI 1.1.0 for Linux x86 (64-bit)
Result Information
| User | AABADAWI |
| Upload Date | April 10 2025 07:52 AM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i5-9400F |
| System Information | |
|---|---|
| Operating System | Kali GNU/Linux Rolling |
| Model | innotek GmbH VirtualBox |
| Motherboard | Oracle Corporation VirtualBox |
| CPU Information | |
|---|---|
| Name | Intel Core i5-9400F |
| Topology | 1 Processor, 6 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 10 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 1.93 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
23
4.34 IPS |
|
|
Image Classification (HP)
|
100% |
24
4.47 IPS |
|
|
Image Classification (Q)
|
97% |
19
3.50 IPS |
|
|
Image Segmentation (SP)
|
100% |
33
0.53 IPS |
|
|
Image Segmentation (HP)
|
100% |
33
0.53 IPS |
|
|
Image Segmentation (Q)
|
98% |
25
0.41 IPS |
|
|
Pose Estimation (SP)
|
100% |
39
0.05 IPS |
|
|
Pose Estimation (HP)
|
100% |
41
0.05 IPS |
|
|
Pose Estimation (Q)
|
96% |
34
0.04 IPS |
|
|
Object Detection (SP)
|
100% |
25
1.96 IPS |
|
|
Object Detection (HP)
|
100% |
25
1.96 IPS |
|
|
Object Detection (Q)
|
87% |
19
1.56 IPS |
|
|
Face Detection (SP)
|
100% |
85
1.01 IPS |
|
|
Face Detection (HP)
|
100% |
84
1.00 IPS |
|
|
Face Detection (Q)
|
97% |
64
0.76 IPS |
|
|
Depth Estimation (SP)
|
100% |
60
0.47 IPS |
|
|
Depth Estimation (HP)
|
99% |
60
0.47 IPS |
|
|
Depth Estimation (Q)
|
64% |
40
0.37 IPS |
|
|
Style Transfer (SP)
|
100% |
127
0.16 IPS |
|
|
Style Transfer (HP)
|
100% |
127
0.16 IPS |
|
|
Style Transfer (Q)
|
98% |
103
0.13 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
27
1.00 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27
1.01 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
21
0.79 IPS |
|
|
Text Classification (SP)
|
100% |
33
44.2 IPS |
|
|
Text Classification (HP)
|
100% |
33
44.0 IPS |
|
|
Text Classification (Q)
|
91% |
25
33.4 IPS |
|
|
Machine Translation (SP)
|
100% |
57
0.98 IPS |
|
|
Machine Translation (HP)
|
100% |
57
0.98 IPS |
|
|
Machine Translation (Q)
|
58% |
30
0.72 IPS |
