Vultr VCG
Geekbench ML Score
741
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | June 11 2024 07:21 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, 6 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 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 4.00 MB x 3 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 29.37 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
533
99.8 IPS |
|
|
Image Classification (F16)
|
100% |
528
98.8 IPS |
|
|
Image Classification (I8)
|
99% |
287
53.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
789
13.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
803
13.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
367
6.13 IPS |
|
|
Pose Estimation (F32)
|
100% |
1024
1.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
1026
1.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
733
0.89 IPS |
|
|
Object Detection (F32)
|
100% |
591
44.1 IPS |
|
|
Object Detection (F16)
|
100% |
595
44.4 IPS |
|
|
Object Detection (I8)
|
65% |
322
24.0 IPS |
|
|
Face Detection (F32)
|
100% |
1293
15.4 IPS |
|
|
Face Detection (F16)
|
100% |
1313
15.6 IPS |
|
|
Face Detection (I8)
|
87% |
824
9.80 IPS |
|
|
Depth Estimation (F32)
|
100% |
1145
8.88 IPS |
|
|
Depth Estimation (F16)
|
100% |
1162
9.01 IPS |
|
|
Depth Estimation (I8)
|
95% |
773
6.00 IPS |
|
|
Style Transfer (F32)
|
100% |
1648
2.17 IPS |
|
|
Style Transfer (F16)
|
100% |
1652
2.17 IPS |
|
|
Style Transfer (I8)
|
98% |
1741
2.29 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
644
23.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
626
22.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
480
17.1 IPS |
|
|
Text Classification (F32)
|
100% |
613
880.8 IPS |
|
|
Text Classification (F16)
|
100% |
628
902.7 IPS |
|
|
Text Classification (I8)
|
92% |
272
390.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1130
20.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1124
20.7 IPS |
|
|
Machine Translation (I8)
|
62% |
433
7.96 IPS |
