Inversenet Inc. FRONTIER
Geekbench AI Score
2737
Single Precision Score
1189
Half Precision Score
4441
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | July 01 2025 09:16 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 7 5700X |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Inversenet Inc. FRONTIER |
| Motherboard | ASRock B550M-HDV/I |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5700X |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 33 Stepping 2 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2834
527.1 IPS |
|
|
Image Classification (HP)
|
100% |
570
106.0 IPS |
|
|
Image Classification (Q)
|
96% |
4863
908.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1803
29.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
755
12.2 IPS |
|
|
Image Segmentation (Q)
|
97% |
5709
92.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
4598
5.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
3110
3.63 IPS |
|
|
Pose Estimation (Q)
|
86% |
7555
8.93 IPS |
|
|
Object Detection (SP)
|
100% |
1564
124.1 IPS |
|
|
Object Detection (HP)
|
100% |
544
43.2 IPS |
|
|
Object Detection (Q)
|
58% |
2611
285.3 IPS |
|
|
Face Detection (SP)
|
100% |
3843
45.7 IPS |
|
|
Face Detection (HP)
|
100% |
1186
14.1 IPS |
|
|
Face Detection (Q)
|
96% |
6331
75.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
4889
37.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
1522
11.7 IPS |
|
|
Depth Estimation (Q)
|
78% |
7237
57.7 IPS |
|
|
Style Transfer (SP)
|
100% |
9079
11.7 IPS |
|
|
Style Transfer (HP)
|
100% |
7131
9.17 IPS |
|
|
Style Transfer (Q)
|
87% |
11396
14.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1665
61.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1426
52.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3221
119.3 IPS |
|
|
Text Classification (SP)
|
100% |
1278
1.71 KIPS |
|
|
Text Classification (HP)
|
100% |
657
876.8 IPS |
|
|
Text Classification (Q)
|
97% |
1352
1.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
1771
30.5 IPS |
|
|
Machine Translation (HP)
|
100% |
647
11.2 IPS |
|
|
Machine Translation (Q)
|
68% |
2401
46.4 IPS |
