INTEL X99
Geekbench ML Score
2540
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | November 20 2024 04:52 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Windows 11 Pro (64-bit) |
| Model | INTEL X99 |
| Motherboard | INTEL X99 |
| CPU Information | |
|---|---|
| Name | Intel Xeon E5-2695 v3 |
| Topology | 2 Processors, 28 Cores, 56 Threads |
| Identifier | GenuineIntel Family 6 Model 63 Stepping 2 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 28 Cores |
| L1 Instruction Cache | 32.0 KB x 14 |
| L1 Data Cache | 32.0 KB x 14 |
| L2 Cache | 256 KB x 14 |
| L3 Cache | 35.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1269
237.5 IPS |
|
|
Image Classification (F16)
|
100% |
1310
245.1 IPS |
|
|
Image Classification (I8)
|
97% |
1703
318.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1042
17.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1060
17.7 IPS |
|
|
Image Segmentation (I8)
|
97% |
1514
25.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
13300
16.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
13276
16.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
12979
15.7 IPS |
|
|
Object Detection (F32)
|
100% |
1212
90.5 IPS |
|
|
Object Detection (F16)
|
100% |
1214
90.6 IPS |
|
|
Object Detection (I8)
|
60% |
903
67.4 IPS |
|
|
Face Detection (F32)
|
100% |
2625
31.2 IPS |
|
|
Face Detection (F16)
|
100% |
2623
31.2 IPS |
|
|
Face Detection (I8)
|
87% |
2275
27.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
7366
57.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
7387
57.3 IPS |
|
|
Depth Estimation (I8)
|
74% |
7887
61.2 IPS |
|
|
Style Transfer (F32)
|
100% |
21400
28.1 IPS |
|
|
Style Transfer (F16)
|
100% |
21401
28.2 IPS |
|
|
Style Transfer (I8)
|
85% |
11132
14.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2271
81.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2283
81.5 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
2085
74.5 IPS |
|
|
Text Classification (F32)
|
100% |
802
1.15 KIPS |
|
|
Text Classification (F16)
|
100% |
802
1.15 KIPS |
|
|
Text Classification (I8)
|
94% |
260
373.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1047
19.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1044
19.2 IPS |
|
|
Machine Translation (I8)
|
67% |
1442
26.5 IPS |
