System manufacturer System Product Name
Geekbench AI Score
7112
Single Precision Score
6964
Half Precision Score
9305
Quantized Score
Geekbench AI 1.4.0 Corporate for Windows AVX2
Result Information
| User | meoow |
| Upload Date | August 23 2025 05:40 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | AMD Ryzen 9 5950X 16-Core Processor |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Enterprise (64-bit) |
| Model | System manufacturer System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. TUF GAMING X570-PLUS (WI-FI) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 5950X |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 25 Model 33 Stepping 2 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4077
758.1 IPS |
|
|
Image Classification (HP)
|
100% |
4156
772.9 IPS |
|
|
Image Classification (Q)
|
100% |
6447
1.20 KIPS |
|
|
Image Segmentation (SP)
|
100% |
5869
95.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
5615
91.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
10289
167.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
11722
13.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
11749
13.7 IPS |
|
|
Pose Estimation (Q)
|
94% |
26963
31.6 IPS |
|
|
Object Detection (SP)
|
100% |
4478
355.2 IPS |
|
|
Object Detection (HP)
|
100% |
4449
352.9 IPS |
|
|
Object Detection (Q)
|
87% |
7249
581.4 IPS |
|
|
Face Detection (SP)
|
100% |
10552
125.4 IPS |
|
|
Face Detection (HP)
|
100% |
10544
125.3 IPS |
|
|
Face Detection (Q)
|
97% |
21278
253.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
11988
92.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
11811
91.0 IPS |
|
|
Depth Estimation (Q)
|
81% |
22773
179.6 IPS |
|
|
Style Transfer (SP)
|
100% |
33613
43.2 IPS |
|
|
Style Transfer (HP)
|
100% |
33557
43.1 IPS |
|
|
Style Transfer (Q)
|
98% |
74984
96.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6392
236.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6472
239.0 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
13001
481.6 IPS |
|
|
Text Classification (SP)
|
100% |
3006
4.01 KIPS |
|
|
Text Classification (HP)
|
100% |
2791
3.73 KIPS |
|
|
Text Classification (Q)
|
91% |
273
367.5 IPS |
|
|
Machine Translation (SP)
|
100% |
3230
55.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2914
50.2 IPS |
|
|
Machine Translation (Q)
|
100% |
2912
50.2 IPS |
