GTX 960 INTEL X99
Geekbench ML Score
3053
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | saiht |
| Upload Date | July 25 2024 12:06 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | INTEL X99 |
| Motherboard | INTEL X99 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Xeon E5-2696 v3 |
| Topology | 1 Processor, 18 Cores, 36 Threads |
| Identifier | GenuineIntel Family 6 Model 63 Stepping 2 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 18 Cores |
| L1 Instruction Cache | 32.0 KB x 18 |
| L1 Data Cache | 32.0 KB x 18 |
| L2 Cache | 256 KB x 18 |
| L3 Cache | 45.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce GTX 960 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1379
258.0 IPS |
|
|
Image Classification (F16)
|
100% |
1381
258.4 IPS |
|
|
Image Classification (I8)
|
100% |
1059
198.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1938
32.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1941
32.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1569
26.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
12958
15.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
12892
15.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
11068
13.4 IPS |
|
|
Object Detection (F32)
|
100% |
1448
108.1 IPS |
|
|
Object Detection (F16)
|
100% |
1441
107.6 IPS |
|
|
Object Detection (I8)
|
60% |
1222
91.2 IPS |
|
|
Face Detection (F32)
|
100% |
2943
35.0 IPS |
|
|
Face Detection (F16)
|
100% |
2960
35.2 IPS |
|
|
Face Detection (I8)
|
89% |
2219
26.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
6805
52.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
6812
52.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
5351
41.5 IPS |
|
|
Style Transfer (F32)
|
100% |
22448
29.5 IPS |
|
|
Style Transfer (F16)
|
100% |
22660
29.8 IPS |
|
|
Style Transfer (I8)
|
98% |
18710
24.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5442
194.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4983
177.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3635
129.8 IPS |
|
|
Text Classification (F32)
|
100% |
1023
1.47 KIPS |
|
|
Text Classification (F16)
|
100% |
989
1.42 KIPS |
|
|
Text Classification (I8)
|
98% |
573
823.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1666
30.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1669
30.7 IPS |
|
|
Machine Translation (I8)
|
70% |
862
15.9 IPS |
