Trigkey Green G5
Geekbench AI Score
27
Single Precision Score
27
Half Precision Score
19
Quantized Score
Geekbench AI 1.2.0 for Linux x86 (64-bit)
Result Information
| Upload Date | December 30 2024 09:51 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel N100 |
| System Information | |
|---|---|
| Operating System | Pop!_OS 22.04 LTS |
| Model | Trigkey Green G5 |
| Motherboard | Trigkey Green G5 |
| CPU Information | |
|---|---|
| Name | Intel N100 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 190 Stepping 0 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.40 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
16
2.95 IPS |
|
|
Image Classification (HP)
|
100% |
16
2.93 IPS |
|
|
Image Classification (Q)
|
97% |
12
2.21 IPS |
|
|
Image Segmentation (SP)
|
100% |
21
0.34 IPS |
|
|
Image Segmentation (HP)
|
100% |
21
0.34 IPS |
|
|
Image Segmentation (Q)
|
98% |
16
0.26 IPS |
|
|
Pose Estimation (SP)
|
100% |
24
0.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
24
0.03 IPS |
|
|
Pose Estimation (Q)
|
96% |
19
0.02 IPS |
|
|
Object Detection (SP)
|
100% |
15
1.21 IPS |
|
|
Object Detection (HP)
|
100% |
15
1.19 IPS |
|
|
Object Detection (Q)
|
87% |
11
0.92 IPS |
|
|
Face Detection (SP)
|
100% |
50
0.59 IPS |
|
|
Face Detection (HP)
|
100% |
50
0.59 IPS |
|
|
Face Detection (Q)
|
97% |
38
0.45 IPS |
|
|
Depth Estimation (SP)
|
100% |
36
0.28 IPS |
|
|
Depth Estimation (HP)
|
99% |
36
0.27 IPS |
|
|
Depth Estimation (Q)
|
64% |
23
0.22 IPS |
|
|
Style Transfer (SP)
|
100% |
75
0.10 IPS |
|
|
Style Transfer (HP)
|
100% |
75
0.10 IPS |
|
|
Style Transfer (Q)
|
98% |
59
0.08 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
16
0.60 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16
0.60 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
12
0.46 IPS |
|
|
Text Classification (SP)
|
100% |
21
27.9 IPS |
|
|
Text Classification (HP)
|
100% |
21
27.6 IPS |
|
|
Text Classification (Q)
|
91% |
15
20.0 IPS |
|
|
Machine Translation (SP)
|
100% |
39
0.68 IPS |
|
|
Machine Translation (HP)
|
100% |
39
0.66 IPS |
|
|
Machine Translation (Q)
|
58% |
20
0.48 IPS |
