ASUSTeK COMPUTER INC. ROG Strix G634JZ_G634JZ
Geekbench AI Score
22350
Single Precision Score
34305
Half Precision Score
17555
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | January 04 2025 01:12 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | ASUSTeK COMPUTER INC. ROG Strix G634JZ_G634JZ |
| Motherboard | ASUSTeK COMPUTER INC. G634JZ |
| Power Plan | Silent |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13980HX |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
8727
1.62 KIPS |
|
|
Image Classification (HP)
|
99% |
14409
2.69 KIPS |
|
|
Image Classification (Q)
|
100% |
7885
1.47 KIPS |
|
|
Image Segmentation (SP)
|
100% |
13088
212.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
16669
270.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
12292
199.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
138536
161.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
356508
416.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
125398
146.9 IPS |
|
|
Object Detection (SP)
|
100% |
10396
824.6 IPS |
|
|
Object Detection (HP)
|
100% |
16616
1.32 KIPS |
|
|
Object Detection (Q)
|
85% |
9614
773.9 IPS |
|
|
Face Detection (SP)
|
100% |
29626
352.0 IPS |
|
|
Face Detection (HP)
|
100% |
38039
452.0 IPS |
|
|
Face Detection (Q)
|
97% |
26272
313.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
55518
427.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
96324
744.2 IPS |
|
|
Depth Estimation (Q)
|
77% |
43670
349.1 IPS |
|
|
Style Transfer (SP)
|
100% |
252383
324.4 IPS |
|
|
Style Transfer (HP)
|
100% |
595024
764.9 IPS |
|
|
Style Transfer (Q)
|
98% |
216803
279.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
37775
1.39 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
47200
1.74 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
27867
1.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3380
4.51 KIPS |
|
|
Text Classification (HP)
|
99% |
4320
5.77 KIPS |
|
|
Text Classification (Q)
|
97% |
1796
2.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
3568
61.5 IPS |
|
|
Machine Translation (HP)
|
100% |
3569
61.5 IPS |
|
|
Machine Translation (Q)
|
70% |
1912
35.9 IPS |
