IMATX-Q670-P29 A_M_I_
Geekbench AI Score
24701
Single Precision Score
50517
Half Precision Score
53401
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 30 2025 01:27 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) B580 Graphics (dGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | IMATX-Q670-P29 A_M_I_ |
| Motherboard | BIOSTAR Group IMATX-Q670-P29 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900K |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12874
2.39 KIPS |
|
|
Image Classification (HP)
|
100% |
26581
4.94 KIPS |
|
|
Image Classification (Q)
|
100% |
30364
5.65 KIPS |
|
|
Image Segmentation (SP)
|
100% |
22916
371.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
37142
602.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
38173
618.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
83321
97.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
353001
411.9 IPS |
|
|
Pose Estimation (Q)
|
97% |
651597
762.9 IPS |
|
|
Object Detection (SP)
|
100% |
10506
833.4 IPS |
|
|
Object Detection (HP)
|
100% |
27236
2.16 KIPS |
|
|
Object Detection (Q)
|
88% |
22885
1.83 KIPS |
|
|
Face Detection (SP)
|
100% |
28463
338.2 IPS |
|
|
Face Detection (HP)
|
100% |
54050
642.2 IPS |
|
|
Face Detection (Q)
|
100% |
56798
674.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
61992
477.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
135955
1.05 KIPS |
|
|
Depth Estimation (Q)
|
89% |
163070
1.27 KIPS |
|
|
Style Transfer (SP)
|
100% |
186260
239.4 IPS |
|
|
Style Transfer (HP)
|
100% |
585058
752.1 IPS |
|
|
Style Transfer (Q)
|
98% |
640673
826.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
33323
1.23 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
80033
2.96 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
77382
2.87 KIPS |
|
|
Text Classification (SP)
|
100% |
6264
8.36 KIPS |
|
|
Text Classification (HP)
|
100% |
5806
7.75 KIPS |
|
|
Text Classification (Q)
|
92% |
4149
5.57 KIPS |
|
|
Machine Translation (SP)
|
100% |
4773
82.2 IPS |
|
|
Machine Translation (HP)
|
100% |
5709
98.3 IPS |
|
|
Machine Translation (Q)
|
100% |
5727
98.6 IPS |
