Vultr VCG
Geekbench ML Score
329
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | June 11 2024 07:22 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, 1 Core, 2 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 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 4.00 MB x 1 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 7.75 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
232
43.4 IPS |
|
|
Image Classification (F16)
|
100% |
230
43.1 IPS |
|
|
Image Classification (I8)
|
99% |
128
24.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
323
5.39 IPS |
|
|
Image Segmentation (F16)
|
100% |
323
5.39 IPS |
|
|
Image Segmentation (I8)
|
98% |
153
2.56 IPS |
|
|
Pose Estimation (F32)
|
100% |
412
0.50 IPS |
|
|
Pose Estimation (F16)
|
100% |
357
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
269
0.33 IPS |
|
|
Object Detection (F32)
|
100% |
266
19.9 IPS |
|
|
Object Detection (F16)
|
100% |
266
19.9 IPS |
|
|
Object Detection (I8)
|
65% |
142
10.6 IPS |
|
|
Face Detection (F32)
|
100% |
580
6.89 IPS |
|
|
Face Detection (F16)
|
100% |
562
6.69 IPS |
|
|
Face Detection (I8)
|
87% |
345
4.10 IPS |
|
|
Depth Estimation (F32)
|
100% |
421
3.26 IPS |
|
|
Depth Estimation (F16)
|
100% |
485
3.76 IPS |
|
|
Depth Estimation (I8)
|
95% |
291
2.26 IPS |
|
|
Style Transfer (F32)
|
100% |
721
0.95 IPS |
|
|
Style Transfer (F16)
|
100% |
712
0.94 IPS |
|
|
Style Transfer (I8)
|
98% |
685
0.90 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
298
10.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
313
11.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
184
6.56 IPS |
|
|
Text Classification (F32)
|
100% |
377
541.5 IPS |
|
|
Text Classification (F16)
|
100% |
377
541.6 IPS |
|
|
Text Classification (I8)
|
92% |
170
244.3 IPS |
|
|
Machine Translation (F32)
|
100% |
534
9.83 IPS |
|
|
Machine Translation (F16)
|
100% |
559
10.3 IPS |
|
|
Machine Translation (I8)
|
62% |
272
5.01 IPS |
