EVGA Corp. Z690 CLASSIFIED
Geekbench AI Score
33233
Single Precision Score
47946
Half Precision Score
25454
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | TallonRain |
| Upload Date | July 29 2025 01:32 AM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 SUPER |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro for Workstations (64-bit) |
| Model | EVGA Corp. Z690 CLASSIFIED |
| Motherboard | EVGA Corp. Z690 CLASSIFIED |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i9-12900K |
| Topology | 1 Processor, 16 Cores, 24 Threads |
| Identifier | GenuineIntel Family 6 Model 151 Stepping 2 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12364
2.30 KIPS |
|
|
Image Classification (HP)
|
99% |
17524
3.27 KIPS |
|
|
Image Classification (Q)
|
100% |
10204
1.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
22574
365.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
29195
473.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
20558
334.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
260542
304.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
490558
572.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
219347
257.0 IPS |
|
|
Object Detection (SP)
|
100% |
16217
1.29 KIPS |
|
|
Object Detection (HP)
|
100% |
21386
1.70 KIPS |
|
|
Object Detection (Q)
|
85% |
13811
1.11 KIPS |
|
|
Face Detection (SP)
|
100% |
46216
549.1 IPS |
|
|
Face Detection (HP)
|
100% |
60736
721.7 IPS |
|
|
Face Detection (Q)
|
97% |
40511
483.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
81508
628.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
139901
1.08 KIPS |
|
|
Depth Estimation (Q)
|
78% |
62064
495.6 IPS |
|
|
Style Transfer (SP)
|
100% |
381002
489.8 IPS |
|
|
Style Transfer (HP)
|
100% |
836711
1.08 KIPS |
|
|
Style Transfer (Q)
|
98% |
330734
426.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
49473
1.83 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
70484
2.60 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37530
1.39 KIPS |
|
|
Text Classification (SP)
|
100% |
3433
4.58 KIPS |
|
|
Text Classification (HP)
|
99% |
4257
5.68 KIPS |
|
|
Text Classification (Q)
|
97% |
2136
2.86 KIPS |
|
|
Machine Translation (SP)
|
100% |
5718
98.5 IPS |
|
|
Machine Translation (HP)
|
100% |
5608
96.6 IPS |
|
|
Machine Translation (Q)
|
70% |
2696
50.6 IPS |
