NEC PC-VK27MCZCJ
Geekbench ML Score
352
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| User | Puffin |
| Upload Date | February 29 2024 07:19 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Ubuntu 23.10 |
| Model | NEC PC-VK27MCZCJ |
| Motherboard | NEC Sakura2 |
| CPU Information | |
|---|---|
| Name | Intel Core i3-4100M |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 0 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 3.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 9.64 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
263
49.1 IPS |
|
|
Image Classification (F16)
|
100% |
261
48.9 IPS |
|
|
Image Classification (I8)
|
99% |
164
30.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
327
5.47 IPS |
|
|
Image Segmentation (F16)
|
100% |
329
5.49 IPS |
|
|
Image Segmentation (I8)
|
98% |
185
3.09 IPS |
|
|
Pose Estimation (F32)
|
100% |
443
0.54 IPS |
|
|
Pose Estimation (F16)
|
100% |
447
0.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
362
0.44 IPS |
|
|
Object Detection (F32)
|
100% |
276
20.6 IPS |
|
|
Object Detection (F16)
|
100% |
278
20.7 IPS |
|
|
Object Detection (I8)
|
65% |
184
13.8 IPS |
|
|
Face Detection (F32)
|
100% |
505
6.00 IPS |
|
|
Face Detection (F16)
|
100% |
516
6.13 IPS |
|
|
Face Detection (I8)
|
87% |
397
4.73 IPS |
|
|
Depth Estimation (F32)
|
100% |
485
3.76 IPS |
|
|
Depth Estimation (F16)
|
100% |
478
3.70 IPS |
|
|
Depth Estimation (I8)
|
95% |
413
3.20 IPS |
|
|
Style Transfer (F32)
|
100% |
683
0.90 IPS |
|
|
Style Transfer (F16)
|
100% |
677
0.89 IPS |
|
|
Style Transfer (I8)
|
98% |
810
1.07 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
271
9.67 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
277
9.88 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
229
8.18 IPS |
|
|
Text Classification (F32)
|
100% |
407
585.0 IPS |
|
|
Text Classification (F16)
|
100% |
407
584.3 IPS |
|
|
Text Classification (I8)
|
92% |
158
226.5 IPS |
|
|
Machine Translation (F32)
|
100% |
538
9.89 IPS |
|
|
Machine Translation (F16)
|
100% |
547
10.1 IPS |
|
|
Machine Translation (I8)
|
62% |
228
4.20 IPS |
