Vultr VCG
Geekbench ML Score
880
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | June 11 2024 07:18 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Ubuntu 22.04.4 LTS |
| Model | Vultr VCG |
| Motherboard | N/A |
| CPU Information | |
|---|---|
| Name | Intel Core Processor (Broadwell, no TSX, IBRS) |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 61 Stepping 2 |
| Base Frequency | 2.79 GHz |
| Cluster 1 | 0 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 4.00 MB x 4 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 39.16 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
610
114.2 IPS |
|
|
Image Classification (F16)
|
100% |
546
102.2 IPS |
|
|
Image Classification (I8)
|
99% |
328
61.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1059
17.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1007
16.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
459
7.66 IPS |
|
|
Pose Estimation (F32)
|
100% |
1230
1.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
1178
1.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
997
1.21 IPS |
|
|
Object Detection (F32)
|
100% |
752
56.1 IPS |
|
|
Object Detection (F16)
|
100% |
731
54.5 IPS |
|
|
Object Detection (I8)
|
65% |
478
35.7 IPS |
|
|
Face Detection (F32)
|
100% |
1439
17.1 IPS |
|
|
Face Detection (F16)
|
100% |
1557
18.5 IPS |
|
|
Face Detection (I8)
|
87% |
1041
12.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1316
10.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
1312
10.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
1015
7.87 IPS |
|
|
Style Transfer (F32)
|
100% |
1678
2.21 IPS |
|
|
Style Transfer (F16)
|
100% |
1661
2.19 IPS |
|
|
Style Transfer (I8)
|
98% |
2212
2.91 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
802
28.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
823
29.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
621
22.2 IPS |
|
|
Text Classification (F32)
|
100% |
640
919.7 IPS |
|
|
Text Classification (F16)
|
100% |
683
981.2 IPS |
|
|
Text Classification (I8)
|
92% |
359
516.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1189
21.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1161
21.4 IPS |
|
|
Machine Translation (I8)
|
62% |
487
8.97 IPS |
