Vultr VCG
Geekbench ML Score
789
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, 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 | 62.79 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
525
98.3 IPS |
|
|
Image Classification (F16)
|
100% |
528
98.9 IPS |
|
|
Image Classification (I8)
|
99% |
288
54.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
872
14.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
865
14.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
368
6.15 IPS |
|
|
Pose Estimation (F32)
|
100% |
1098
1.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
1095
1.33 IPS |
|
|
Pose Estimation (I8)
|
100% |
753
0.91 IPS |
|
|
Object Detection (F32)
|
100% |
619
46.2 IPS |
|
|
Object Detection (F16)
|
100% |
616
46.0 IPS |
|
|
Object Detection (I8)
|
65% |
333
24.9 IPS |
|
|
Face Detection (F32)
|
100% |
1443
17.2 IPS |
|
|
Face Detection (F16)
|
100% |
1452
17.3 IPS |
|
|
Face Detection (I8)
|
87% |
839
9.97 IPS |
|
|
Depth Estimation (F32)
|
100% |
1269
9.84 IPS |
|
|
Depth Estimation (F16)
|
100% |
1262
9.79 IPS |
|
|
Depth Estimation (I8)
|
95% |
796
6.17 IPS |
|
|
Style Transfer (F32)
|
100% |
1798
2.37 IPS |
|
|
Style Transfer (F16)
|
100% |
1801
2.37 IPS |
|
|
Style Transfer (I8)
|
98% |
1821
2.40 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
836
29.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
825
29.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
488
17.4 IPS |
|
|
Text Classification (F32)
|
100% |
631
906.7 IPS |
|
|
Text Classification (F16)
|
100% |
634
911.7 IPS |
|
|
Text Classification (I8)
|
92% |
273
393.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1244
22.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1198
22.0 IPS |
|
|
Machine Translation (I8)
|
62% |
456
8.39 IPS |
