GIGABYTE P65
Geekbench AI Score
5255
Single Precision Score
5020
Half Precision Score
4012
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | December 22 2025 09:23 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce GTX 1060 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | GIGABYTE P65 |
| Motherboard | GIGABYTE P65 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-7700HQ |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 9 |
| Base Frequency | 2.81 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1983
368.7 IPS |
|
|
Image Classification (HP)
|
100% |
2134
396.8 IPS |
|
|
Image Classification (Q)
|
99% |
1805
336.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
3099
50.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
3161
51.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2523
41.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
19166
22.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
17070
19.9 IPS |
|
|
Pose Estimation (Q)
|
98% |
16918
19.8 IPS |
|
|
Object Detection (SP)
|
100% |
2676
212.2 IPS |
|
|
Object Detection (HP)
|
100% |
2729
216.5 IPS |
|
|
Object Detection (Q)
|
85% |
2248
180.9 IPS |
|
|
Face Detection (SP)
|
100% |
4896
58.2 IPS |
|
|
Face Detection (HP)
|
100% |
5109
60.7 IPS |
|
|
Face Detection (Q)
|
97% |
4189
50.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
9953
76.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
9825
75.9 IPS |
|
|
Depth Estimation (Q)
|
77% |
8120
65.0 IPS |
|
|
Style Transfer (SP)
|
100% |
42110
54.1 IPS |
|
|
Style Transfer (HP)
|
100% |
30284
38.9 IPS |
|
|
Style Transfer (Q)
|
98% |
35235
45.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7313
270.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7197
265.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5394
199.7 IPS |
|
|
Text Classification (SP)
|
100% |
1446
1.93 KIPS |
|
|
Text Classification (HP)
|
100% |
1313
1.75 KIPS |
|
|
Text Classification (Q)
|
97% |
849
1.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
2349
40.5 IPS |
|
|
Machine Translation (HP)
|
96% |
2256
39.0 IPS |
|
|
Machine Translation (Q)
|
70% |
1137
21.3 IPS |
