SLIMBOOK EXCALIBUR-16-AMD7
Geekbench ML Score
2247
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | July 04 2024 01:07 PM |
| Views | 81 |
System Information
| System Information | |
|---|---|
| Operating System | Slimbook OS |
| Model | SLIMBOOK EXCALIBUR-16-AMD7 |
| Motherboard | SLIMBOOK EXCALIBUR-16-AMD7 |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 7840HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 116 Stepping 1 |
| Base Frequency | 5.14 GHz |
| Cluster 1 | 0 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 1.00 MB x 8 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 14.94 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1928
360.8 IPS |
|
|
Image Classification (F16)
|
100% |
1939
362.8 IPS |
|
|
Image Classification (I8)
|
99% |
1350
252.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
2608
43.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
2598
43.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1204
20.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
2855
3.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
2892
3.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
3635
4.40 IPS |
|
|
Object Detection (F32)
|
100% |
2073
154.7 IPS |
|
|
Object Detection (F16)
|
100% |
2079
155.2 IPS |
|
|
Object Detection (I8)
|
65% |
1310
97.8 IPS |
|
|
Face Detection (F32)
|
100% |
2745
32.6 IPS |
|
|
Face Detection (F16)
|
100% |
2730
32.5 IPS |
|
|
Face Detection (I8)
|
87% |
2565
30.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2796
21.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
2800
21.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
2685
20.8 IPS |
|
|
Style Transfer (F32)
|
100% |
3007
3.96 IPS |
|
|
Style Transfer (F16)
|
100% |
2997
3.94 IPS |
|
|
Style Transfer (I8)
|
98% |
6150
8.09 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2053
73.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2043
73.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1855
66.2 IPS |
|
|
Text Classification (F32)
|
100% |
2060
2.96 KIPS |
|
|
Text Classification (F16)
|
100% |
1875
2.69 KIPS |
|
|
Text Classification (I8)
|
92% |
874
1.26 KIPS |
|
|
Machine Translation (F32)
|
100% |
2925
53.8 IPS |
|
|
Machine Translation (F16)
|
100% |
2877
52.9 IPS |
|
|
Machine Translation (I8)
|
62% |
1035
19.1 IPS |
