Vultr VCG
Geekbench ML Score
168
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | June 11 2024 07:26 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, 3 Cores |
| Identifier | GenuineIntel Family 6 Model 61 Stepping 2 |
| Base Frequency | 2.79 GHz |
| Cluster 1 | 0 Cores |
| L1 Instruction Cache | 32.0 KB x 3 |
| L1 Data Cache | 32.0 KB x 3 |
| L2 Cache | 4.00 MB x 3 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 31.33 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
75
14.0 IPS |
|
|
Image Classification (F16)
|
100% |
75
14.1 IPS |
|
|
Image Classification (I8)
|
99% |
68
12.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
243
4.06 IPS |
|
|
Image Segmentation (F16)
|
100% |
250
4.17 IPS |
|
|
Image Segmentation (I8)
|
98% |
165
2.75 IPS |
|
|
Pose Estimation (F32)
|
100% |
616
0.75 IPS |
|
|
Pose Estimation (F16)
|
100% |
646
0.78 IPS |
|
|
Pose Estimation (I8)
|
100% |
478
0.58 IPS |
|
|
Object Detection (F32)
|
100% |
106
7.93 IPS |
|
|
Object Detection (F16)
|
100% |
104
7.77 IPS |
|
|
Object Detection (I8)
|
65% |
86
6.41 IPS |
|
|
Face Detection (F32)
|
100% |
321
3.81 IPS |
|
|
Face Detection (F16)
|
100% |
315
3.74 IPS |
|
|
Face Detection (I8)
|
87% |
243
2.89 IPS |
|
|
Depth Estimation (F32)
|
100% |
322
2.49 IPS |
|
|
Depth Estimation (F16)
|
100% |
360
2.79 IPS |
|
|
Depth Estimation (I8)
|
95% |
297
2.30 IPS |
|
|
Style Transfer (F32)
|
100% |
1079
1.42 IPS |
|
|
Style Transfer (F16)
|
100% |
1069
1.41 IPS |
|
|
Style Transfer (I8)
|
98% |
1132
1.49 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
186
6.66 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
192
6.87 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
167
5.95 IPS |
|
|
Text Classification (F32)
|
100% |
15
21.5 IPS |
|
|
Text Classification (F16)
|
100% |
15
21.4 IPS |
|
|
Text Classification (I8)
|
92% |
16
22.4 IPS |
|
|
Machine Translation (F32)
|
100% |
75
1.38 IPS |
|
|
Machine Translation (F16)
|
100% |
76
1.39 IPS |
|
|
Machine Translation (I8)
|
62% |
72
1.32 IPS |
