ASUS System Product Name
Geekbench ML Score
14807
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | December 22 2023 12:06 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. PRIME Z490-P |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i9-10900K |
| Topology | 1 Processor, 10 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 5 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 10 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 32.0 KB x 10 |
| L2 Cache | 256 KB x 10 |
| L3 Cache | 20.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3080 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6591
1.23 KIPS |
|
|
Image Classification (F16)
|
100% |
6736
1.26 KIPS |
|
|
Image Classification (I8)
|
100% |
4841
905.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
10675
178.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
10899
182.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
8469
141.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
121921
147.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
122247
148.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
96321
116.6 IPS |
|
|
Object Detection (F32)
|
100% |
4761
355.4 IPS |
|
|
Object Detection (F16)
|
100% |
4710
351.6 IPS |
|
|
Object Detection (I8)
|
56% |
3954
295.2 IPS |
|
|
Face Detection (F32)
|
100% |
22040
262.1 IPS |
|
|
Face Detection (F16)
|
100% |
22664
269.5 IPS |
|
|
Face Detection (I8)
|
89% |
16191
192.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
47570
368.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
47316
366.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
31488
244.2 IPS |
|
|
Style Transfer (F32)
|
100% |
219743
289.1 IPS |
|
|
Style Transfer (F16)
|
100% |
215493
283.5 IPS |
|
|
Style Transfer (I8)
|
98% |
161871
212.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
30307
1.08 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
30538
1.09 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
18028
643.8 IPS |
|
|
Text Classification (F32)
|
100% |
2288
3.29 KIPS |
|
|
Text Classification (F16)
|
100% |
2301
3.31 KIPS |
|
|
Text Classification (I8)
|
98% |
1052
1.51 KIPS |
|
|
Machine Translation (F32)
|
100% |
2873
52.9 IPS |
|
|
Machine Translation (F16)
|
100% |
2880
53.0 IPS |
|
|
Machine Translation (I8)
|
70% |
1438
26.5 IPS |
