innotek GmbH VirtualBox
Geekbench AI Score
481
Single Precision Score
246
Half Precision Score
169
Quantized Score
Geekbench AI 1.3.0 for Linux AVX2
Result Information
| Upload Date | April 09 2025 06:46 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i7-9700 |
| System Information | |
|---|---|
| Operating System | Kali GNU/Linux Rolling |
| Model | innotek GmbH VirtualBox |
| Motherboard | Oracle Corporation VirtualBox |
| CPU Information | |
|---|---|
| Name | Intel Core i7-9700 |
| Topology | 1 Processor, 6 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 13 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 7.76 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
969
180.2 IPS |
|
|
Image Classification (HP)
|
100% |
1020
189.7 IPS |
|
|
Image Classification (Q)
|
99% |
171
31.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
344
5.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
337
5.47 IPS |
|
|
Image Segmentation (Q)
|
98% |
230
3.74 IPS |
|
|
Pose Estimation (SP)
|
100% |
793
0.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
782
0.91 IPS |
|
|
Pose Estimation (Q)
|
96% |
831
0.97 IPS |
|
|
Object Detection (SP)
|
100% |
677
53.7 IPS |
|
|
Object Detection (HP)
|
100% |
577
45.8 IPS |
|
|
Object Detection (Q)
|
85% |
171
13.8 IPS |
|
|
Face Detection (SP)
|
100% |
334
3.97 IPS |
|
|
Face Detection (HP)
|
100% |
311
3.70 IPS |
|
|
Face Detection (Q)
|
97% |
340
4.05 IPS |
|
|
Depth Estimation (SP)
|
100% |
368
2.83 IPS |
|
|
Depth Estimation (HP)
|
99% |
413
3.18 IPS |
|
|
Depth Estimation (Q)
|
63% |
328
3.08 IPS |
|
|
Style Transfer (SP)
|
100% |
1022
1.31 IPS |
|
|
Style Transfer (HP)
|
100% |
1046
1.34 IPS |
|
|
Style Transfer (Q)
|
98% |
1978
2.55 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1002
37.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
113
4.19 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
110
4.08 IPS |
|
|
Text Classification (SP)
|
100% |
1295
1.73 KIPS |
|
|
Text Classification (HP)
|
100% |
17
22.2 IPS |
|
|
Text Classification (Q)
|
92% |
11
15.1 IPS |
|
|
Machine Translation (SP)
|
100% |
23
0.40 IPS |
|
|
Machine Translation (HP)
|
100% |
21
0.37 IPS |
|
|
Machine Translation (Q)
|
58% |
13
0.31 IPS |
