Framework Laptop 16 (AMD Ryzen 7040 Series)
Geekbench AI Score
2352
Single Precision Score
2373
Half Precision Score
1632
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| User | bobolopolis |
| Upload Date | December 22 2024 08:07 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Ryzen 9 7940HS |
| System Information | |
|---|---|
| Operating System | Gentoo Linux |
| Model | Framework Laptop 16 (AMD Ryzen 7040 Series) |
| Motherboard | Framework FRANMZCP09 |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 7940HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 116 Stepping 1 |
| Base Frequency | 5.26 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 54.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1635
304.1 IPS |
|
|
Image Classification (HP)
|
100% |
1636
304.3 IPS |
|
|
Image Classification (Q)
|
99% |
1276
238.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2391
38.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2448
39.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1138
18.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2774
3.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
2804
3.27 IPS |
|
|
Pose Estimation (Q)
|
96% |
3287
3.85 IPS |
|
|
Object Detection (SP)
|
100% |
1792
142.1 IPS |
|
|
Object Detection (HP)
|
100% |
1797
142.5 IPS |
|
|
Object Detection (Q)
|
85% |
1111
89.4 IPS |
|
|
Face Detection (SP)
|
100% |
2917
34.7 IPS |
|
|
Face Detection (HP)
|
100% |
2932
34.8 IPS |
|
|
Face Detection (Q)
|
97% |
2459
29.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
2874
22.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
2886
22.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
1999
18.7 IPS |
|
|
Style Transfer (SP)
|
100% |
3504
4.50 IPS |
|
|
Style Transfer (HP)
|
100% |
3514
4.52 IPS |
|
|
Style Transfer (Q)
|
98% |
5901
7.61 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1703
62.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1706
63.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1520
56.3 IPS |
|
|
Text Classification (SP)
|
100% |
1931
2.58 KIPS |
|
|
Text Classification (HP)
|
100% |
1939
2.59 KIPS |
|
|
Text Classification (Q)
|
92% |
840
1.13 KIPS |
|
|
Machine Translation (SP)
|
100% |
2764
47.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2860
49.3 IPS |
|
|
Machine Translation (Q)
|
58% |
686
16.1 IPS |
