Micro-Star International Co., Ltd. Raider GE76 12UE
Geekbench ML Score
10671
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | SpaceAceTACP |
| Upload Date | December 21 2023 11:23 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. Raider GE76 12UE |
| Motherboard | Micro-Star International Co., Ltd. MS-17K4 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i9-12900H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 3 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 48.0 KB x 10 |
| L2 Cache | 1.25 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3060 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4868
910.9 IPS |
|
|
Image Classification (F16)
|
100% |
5215
975.9 IPS |
|
|
Image Classification (I8)
|
100% |
3591
671.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
7647
127.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
7702
128.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
6118
102.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
64355
77.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
66738
80.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
50515
61.2 IPS |
|
|
Object Detection (F32)
|
100% |
4669
348.6 IPS |
|
|
Object Detection (F16)
|
100% |
4711
351.7 IPS |
|
|
Object Detection (I8)
|
63% |
3958
295.5 IPS |
|
|
Face Detection (F32)
|
100% |
14301
170.0 IPS |
|
|
Face Detection (F16)
|
100% |
14382
171.0 IPS |
|
|
Face Detection (I8)
|
89% |
10989
130.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
29019
225.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
27508
213.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
21942
170.2 IPS |
|
|
Style Transfer (F32)
|
100% |
111373
146.5 IPS |
|
|
Style Transfer (F16)
|
100% |
104090
136.9 IPS |
|
|
Style Transfer (I8)
|
98% |
86785
114.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
18939
676.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
19417
693.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
12895
460.5 IPS |
|
|
Text Classification (F32)
|
100% |
2088
3.00 KIPS |
|
|
Text Classification (F16)
|
100% |
2111
3.03 KIPS |
|
|
Text Classification (I8)
|
98% |
1159
1.67 KIPS |
|
|
Machine Translation (F32)
|
100% |
2813
51.8 IPS |
|
|
Machine Translation (F16)
|
100% |
2866
52.7 IPS |
|
|
Machine Translation (I8)
|
70% |
1457
26.8 IPS |
