Inversenet Inc. FRONTIER
Geekbench AI Score
31426
Single Precision Score
53346
Half Precision Score
23830
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | November 13 2025 08:41 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 Ti |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Inversenet Inc. FRONTIER |
| Motherboard | ASRock B760M-HDV/M.2 D4 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-14700F |
| Topology | 1 Processor, 20 Cores, 28 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
13207
2.46 KIPS |
|
|
Image Classification (HP)
|
100% |
19306
3.59 KIPS |
|
|
Image Classification (Q)
|
100% |
11470
2.13 KIPS |
|
|
Image Segmentation (SP)
|
100% |
22448
363.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
31001
502.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
20069
326.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
167049
194.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
653237
762.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
147340
172.6 IPS |
|
|
Object Detection (SP)
|
100% |
15866
1.26 KIPS |
|
|
Object Detection (HP)
|
100% |
24202
1.92 KIPS |
|
|
Object Detection (Q)
|
86% |
13130
1.05 KIPS |
|
|
Face Detection (SP)
|
100% |
44034
523.2 IPS |
|
|
Face Detection (HP)
|
100% |
60217
715.5 IPS |
|
|
Face Detection (Q)
|
97% |
36812
438.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
80077
616.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
144423
1.11 KIPS |
|
|
Depth Estimation (Q)
|
78% |
60799
485.5 IPS |
|
|
Style Transfer (SP)
|
100% |
300855
386.8 IPS |
|
|
Style Transfer (HP)
|
100% |
970711
1.25 KIPS |
|
|
Style Transfer (Q)
|
98% |
251772
324.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
46439
1.71 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
76140
2.81 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
35089
1.30 KIPS |
|
|
Text Classification (SP)
|
100% |
3953
5.28 KIPS |
|
|
Text Classification (HP)
|
100% |
5026
6.71 KIPS |
|
|
Text Classification (Q)
|
97% |
2396
3.21 KIPS |
|
|
Machine Translation (SP)
|
100% |
6141
105.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6106
105.2 IPS |
|
|
Machine Translation (Q)
|
70% |
2800
52.5 IPS |
