Vultr VCG
Geekbench ML Score
589
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | June 11 2024 07:16 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, 2 Cores, 4 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 4 |
| L1 Data Cache | 32.0 KB x 4 |
| L2 Cache | 4.00 MB x 2 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 19.52 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
464
86.8 IPS |
|
|
Image Classification (F16)
|
100% |
465
87.1 IPS |
|
|
Image Classification (I8)
|
99% |
246
46.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
611
10.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
595
9.94 IPS |
|
|
Image Segmentation (I8)
|
98% |
279
4.66 IPS |
|
|
Pose Estimation (F32)
|
100% |
694
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
697
0.84 IPS |
|
|
Pose Estimation (I8)
|
100% |
517
0.63 IPS |
|
|
Object Detection (F32)
|
100% |
486
36.3 IPS |
|
|
Object Detection (F16)
|
100% |
484
36.1 IPS |
|
|
Object Detection (I8)
|
65% |
266
19.8 IPS |
|
|
Face Detection (F32)
|
100% |
1028
12.2 IPS |
|
|
Face Detection (F16)
|
100% |
1014
12.1 IPS |
|
|
Face Detection (I8)
|
87% |
616
7.32 IPS |
|
|
Depth Estimation (F32)
|
100% |
907
7.04 IPS |
|
|
Depth Estimation (F16)
|
100% |
846
6.56 IPS |
|
|
Depth Estimation (I8)
|
95% |
590
4.57 IPS |
|
|
Style Transfer (F32)
|
100% |
1173
1.54 IPS |
|
|
Style Transfer (F16)
|
100% |
1294
1.70 IPS |
|
|
Style Transfer (I8)
|
98% |
1218
1.60 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
577
20.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
520
18.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
340
12.1 IPS |
|
|
Text Classification (F32)
|
100% |
622
893.6 IPS |
|
|
Text Classification (F16)
|
100% |
618
888.6 IPS |
|
|
Text Classification (I8)
|
92% |
268
384.6 IPS |
|
|
Machine Translation (F32)
|
100% |
861
15.9 IPS |
|
|
Machine Translation (F16)
|
100% |
847
15.6 IPS |
|
|
Machine Translation (I8)
|
62% |
369
6.79 IPS |
