Micro-Star International Co., Ltd. RAIDER GE78HX 13VI
Geekbench AI Score
30890
Single Precision Score
45464
Half Precision Score
23951
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | zenckers81 |
| Upload Date | September 27 2025 05:36 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4090 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro Insider Preview (64-bit) |
| Model | Micro-Star International Co., Ltd. RAIDER GE78HX 13VI |
| Motherboard | Micro-Star International Co., Ltd. MS-17S1 |
| Power Plan | Bitsum Highest Performance |
| 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 | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
12273
2.28 KIPS |
|
|
Image Classification (HP)
|
99% |
17553
3.27 KIPS |
|
|
Image Classification (Q)
|
100% |
10601
1.97 KIPS |
|
|
Image Segmentation (SP)
|
100% |
19122
310.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
23898
387.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
17404
283.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
211503
246.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
454778
530.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
190250
222.9 IPS |
|
|
Object Detection (SP)
|
100% |
14804
1.17 KIPS |
|
|
Object Detection (HP)
|
100% |
20617
1.64 KIPS |
|
|
Object Detection (Q)
|
85% |
12785
1.03 KIPS |
|
|
Face Detection (SP)
|
100% |
41860
497.4 IPS |
|
|
Face Detection (HP)
|
100% |
53605
636.9 IPS |
|
|
Face Detection (Q)
|
97% |
36166
431.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
77878
600.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
139363
1.08 KIPS |
|
|
Depth Estimation (Q)
|
78% |
59322
473.7 IPS |
|
|
Style Transfer (SP)
|
100% |
349614
449.4 IPS |
|
|
Style Transfer (HP)
|
100% |
790475
1.02 KIPS |
|
|
Style Transfer (Q)
|
98% |
308979
398.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
50916
1.88 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
69573
2.57 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
38702
1.43 KIPS |
|
|
Text Classification (SP)
|
100% |
3792
5.06 KIPS |
|
|
Text Classification (HP)
|
99% |
4774
6.37 KIPS |
|
|
Text Classification (Q)
|
97% |
2222
2.98 KIPS |
|
|
Machine Translation (SP)
|
100% |
4892
84.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4891
84.2 IPS |
|
|
Machine Translation (Q)
|
70% |
2429
45.6 IPS |
