ASUS X99-A II ASUS All Series
Geekbench AI Score
937
Single Precision Score
942
Half Precision Score
653
Quantized Score
Geekbench AI 1.7.0 for Linux AVX2
Result Information
| User | almaspite |
| Upload Date | February 25 2026 05:11 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Xeon E5-2630 v3 |
| System Information | |
|---|---|
| Operating System | Ubuntu 25.10 |
| Model | ASUS All Series |
| Motherboard | ASUSTeK COMPUTER INC. X99-A II |
| CPU Information | |
|---|---|
| Name | Intel Xeon E5-2630 v3 |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 63 Stepping 2 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 7.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
873
162.4 IPS |
|
|
Image Classification (HP)
|
100% |
872
162.3 IPS |
|
|
Image Classification (Q)
|
99% |
505
94.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1011
16.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1015
16.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
454
7.38 IPS |
|
|
Pose Estimation (SP)
|
100% |
1004
1.17 IPS |
|
|
Pose Estimation (HP)
|
100% |
1010
1.18 IPS |
|
|
Pose Estimation (Q)
|
96% |
1373
1.61 IPS |
|
|
Object Detection (SP)
|
100% |
861
68.3 IPS |
|
|
Object Detection (HP)
|
100% |
873
69.2 IPS |
|
|
Object Detection (Q)
|
85% |
537
43.3 IPS |
|
|
Face Detection (SP)
|
100% |
945
11.2 IPS |
|
|
Face Detection (HP)
|
100% |
943
11.2 IPS |
|
|
Face Detection (Q)
|
97% |
1060
12.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
960
7.40 IPS |
|
|
Depth Estimation (HP)
|
99% |
959
7.39 IPS |
|
|
Depth Estimation (Q)
|
63% |
901
8.45 IPS |
|
|
Style Transfer (SP)
|
100% |
1002
1.29 IPS |
|
|
Style Transfer (HP)
|
100% |
1002
1.29 IPS |
|
|
Style Transfer (Q)
|
98% |
2190
2.82 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
899
33.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
894
33.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
651
24.1 IPS |
|
|
Text Classification (SP)
|
100% |
959
1.28 KIPS |
|
|
Text Classification (HP)
|
100% |
995
1.33 KIPS |
|
|
Text Classification (Q)
|
92% |
280
376.6 IPS |
|
|
Machine Translation (SP)
|
100% |
878
15.1 IPS |
|
|
Machine Translation (HP)
|
100% |
878
15.1 IPS |
|
|
Machine Translation (Q)
|
58% |
221
5.19 IPS |
