MAINGEAR Vector Pro RTX 3080 (Charger) Micro Electronics Inc MG-VCP17A-3080
Geekbench AI Score
15000
Single Precision Score
23970
Half Precision Score
10280
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | jwatts721 |
| Upload Date | December 21 2025 11:08 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro Electronics Inc MG-VCP17A-3080 |
| Motherboard | MAINGEAR VECTOR Pro 17 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 5900HX |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 80 Stepping 0 |
| Base Frequency | 3.30 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5821
1.08 KIPS |
|
|
Image Classification (HP)
|
99% |
9220
1.72 KIPS |
|
|
Image Classification (Q)
|
100% |
4492
835.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
9516
154.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12612
204.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
7594
123.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
81277
94.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
240504
280.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
69173
81.0 IPS |
|
|
Object Detection (SP)
|
100% |
7985
633.3 IPS |
|
|
Object Detection (HP)
|
100% |
11906
944.4 IPS |
|
|
Object Detection (Q)
|
85% |
5927
477.1 IPS |
|
|
Face Detection (SP)
|
100% |
18033
214.3 IPS |
|
|
Face Detection (HP)
|
100% |
25788
306.4 IPS |
|
|
Face Detection (Q)
|
97% |
14022
167.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
40606
312.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
75502
581.7 IPS |
|
|
Depth Estimation (Q)
|
77% |
27443
219.8 IPS |
|
|
Style Transfer (SP)
|
100% |
139260
179.0 IPS |
|
|
Style Transfer (HP)
|
100% |
355634
457.2 IPS |
|
|
Style Transfer (Q)
|
98% |
114328
147.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
25852
954.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35310
1.30 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
15611
578.1 IPS |
|
|
Text Classification (SP)
|
100% |
2182
2.91 KIPS |
|
|
Text Classification (HP)
|
100% |
2770
3.70 KIPS |
|
|
Text Classification (Q)
|
97% |
1162
1.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
2790
48.1 IPS |
|
|
Machine Translation (HP)
|
100% |
2777
47.8 IPS |
|
|
Machine Translation (Q)
|
70% |
1182
22.2 IPS |
