Gigabyte Technology Co., Ltd. B650M GAMING WIFI6E
Geekbench AI Score
26541
Single Precision Score
45346
Half Precision Score
20970
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 04 2025 12:40 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Gigabyte Technology Co., Ltd. B650M GAMING WIFI6E |
| Motherboard | Gigabyte Technology Co., Ltd. B650M GAMING WIFI6E |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 7600X |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 25 Model 97 Stepping 2 |
| Base Frequency | 4.70 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11044
2.05 KIPS |
|
|
Image Classification (HP)
|
100% |
18653
3.47 KIPS |
|
|
Image Classification (Q)
|
100% |
10071
1.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
15335
248.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
20161
326.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
14416
234.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
166375
194.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
468727
546.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
141407
165.6 IPS |
|
|
Object Detection (SP)
|
100% |
14758
1.17 KIPS |
|
|
Object Detection (HP)
|
100% |
24105
1.91 KIPS |
|
|
Object Detection (Q)
|
83% |
12530
1.01 KIPS |
|
|
Face Detection (SP)
|
100% |
37117
441.0 IPS |
|
|
Face Detection (HP)
|
100% |
53755
638.7 IPS |
|
|
Face Detection (Q)
|
97% |
31627
377.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
69464
535.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
135456
1.04 KIPS |
|
|
Depth Estimation (Q)
|
78% |
54172
432.4 IPS |
|
|
Style Transfer (SP)
|
100% |
232245
298.6 IPS |
|
|
Style Transfer (HP)
|
100% |
778327
1.00 KIPS |
|
|
Style Transfer (Q)
|
98% |
195814
252.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
41337
1.53 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
74064
2.73 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
33320
1.23 KIPS |
|
|
Text Classification (SP)
|
100% |
3795
5.07 KIPS |
|
|
Text Classification (HP)
|
100% |
4547
6.07 KIPS |
|
|
Text Classification (Q)
|
97% |
2381
3.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
4441
76.5 IPS |
|
|
Machine Translation (HP)
|
100% |
4534
78.1 IPS |
|
|
Machine Translation (Q)
|
70% |
2402
45.1 IPS |
