System manufacturer System Product Name
Geekbench AI Score
2440
Single Precision Score
2411
Half Precision Score
1869
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| User | bet2600 |
| Upload Date | December 22 2025 12:23 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Ryzen 9 5950X |
| System Information | |
|---|---|
| Operating System | CachyOS |
| Model | System manufacturer System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. ROG STRIX X570-E GAMING |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 5950X |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 25 Model 33 Stepping 2 |
| Base Frequency | 5.09 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 62.69 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1760
327.3 IPS |
|
|
Image Classification (HP)
|
100% |
1722
320.2 IPS |
|
|
Image Classification (Q)
|
99% |
1285
239.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2909
47.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2872
46.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1310
21.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
3350
3.91 IPS |
|
|
Pose Estimation (HP)
|
100% |
3373
3.94 IPS |
|
|
Pose Estimation (Q)
|
96% |
4568
5.35 IPS |
|
|
Object Detection (SP)
|
100% |
1845
146.3 IPS |
|
|
Object Detection (HP)
|
100% |
1875
148.7 IPS |
|
|
Object Detection (Q)
|
85% |
1546
124.4 IPS |
|
|
Face Detection (SP)
|
100% |
2870
34.1 IPS |
|
|
Face Detection (HP)
|
100% |
2874
34.2 IPS |
|
|
Face Detection (Q)
|
97% |
2886
34.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
2652
20.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
2678
20.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
2291
21.5 IPS |
|
|
Style Transfer (SP)
|
100% |
3251
4.18 IPS |
|
|
Style Transfer (HP)
|
100% |
3247
4.17 IPS |
|
|
Style Transfer (Q)
|
98% |
6789
8.75 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1940
71.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1898
70.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1948
72.2 IPS |
|
|
Text Classification (SP)
|
100% |
1543
2.06 KIPS |
|
|
Text Classification (HP)
|
100% |
1411
1.88 KIPS |
|
|
Text Classification (Q)
|
92% |
742
996.2 IPS |
|
|
Machine Translation (SP)
|
100% |
3199
55.1 IPS |
|
|
Machine Translation (HP)
|
100% |
3174
54.7 IPS |
|
|
Machine Translation (Q)
|
58% |
677
15.9 IPS |
