GIGABYTE GIGABYTE GAMING A16 3VH
Geekbench AI Score
17286
Single Precision Score
32720
Half Precision Score
13691
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | nmiguelcosta |
| Upload Date | October 24 2025 06:20 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5060 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GIGABYTE GIGABYTE GAMING A16 3VH |
| Motherboard | GIGABYTE GIGABYTE GAMING A16 3VH |
| Power Plan | Equilibrado |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 260 w/ Radeon 780M Graphics |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 117 Stepping 2 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
7145
1.33 KIPS |
|
|
Image Classification (HP)
|
100% |
13251
2.46 KIPS |
|
|
Image Classification (Q)
|
99% |
6700
1.25 KIPS |
|
|
Image Segmentation (SP)
|
100% |
12527
203.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
20156
326.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
11493
186.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
84177
98.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
275172
321.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
75137
88.0 IPS |
|
|
Object Detection (SP)
|
100% |
9158
726.4 IPS |
|
|
Object Detection (HP)
|
100% |
16816
1.33 KIPS |
|
|
Object Detection (Q)
|
87% |
8079
648.3 IPS |
|
|
Face Detection (SP)
|
100% |
23563
280.0 IPS |
|
|
Face Detection (HP)
|
100% |
38886
462.1 IPS |
|
|
Face Detection (Q)
|
97% |
20176
240.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
42553
327.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
93214
718.2 IPS |
|
|
Depth Estimation (Q)
|
77% |
34928
279.3 IPS |
|
|
Style Transfer (SP)
|
100% |
128498
165.2 IPS |
|
|
Style Transfer (HP)
|
100% |
412716
530.6 IPS |
|
|
Style Transfer (Q)
|
98% |
110172
142.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
23057
851.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
46465
1.72 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
18134
671.5 IPS |
|
|
Text Classification (SP)
|
100% |
2706
3.61 KIPS |
|
|
Text Classification (HP)
|
100% |
3423
4.57 KIPS |
|
|
Text Classification (Q)
|
97% |
1927
2.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
4296
74.0 IPS |
|
|
Machine Translation (HP)
|
100% |
4783
82.4 IPS |
|
|
Machine Translation (Q)
|
70% |
1825
34.2 IPS |
