Framework Laptop 16 (AMD Ryzen 7040 Series)
Geekbench AI Score
5715
Single Precision Score
5760
Half Precision Score
15972
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | April 13 2025 07:25 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | AMD Ryzen 9 7940HS w/ Radeon 780M Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Framework Laptop 16 (AMD Ryzen 7040 Series) |
| Motherboard | Framework FRANMZCP09 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 7940HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 116 Stepping 1 |
| Base Frequency | 4.00 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 96.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3510
652.8 IPS |
|
|
Image Classification (HP)
|
100% |
3728
693.4 IPS |
|
|
Image Classification (Q)
|
100% |
10608
1.97 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4001
64.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
3920
63.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
10943
177.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7142
8.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
6969
8.13 IPS |
|
|
Pose Estimation (Q)
|
98% |
29106
34.1 IPS |
|
|
Object Detection (SP)
|
100% |
3267
259.1 IPS |
|
|
Object Detection (HP)
|
100% |
3158
250.5 IPS |
|
|
Object Detection (Q)
|
88% |
10801
865.8 IPS |
|
|
Face Detection (SP)
|
100% |
7753
92.1 IPS |
|
|
Face Detection (HP)
|
100% |
7827
93.0 IPS |
|
|
Face Detection (Q)
|
100% |
26298
312.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
9182
70.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
9551
73.6 IPS |
|
|
Depth Estimation (Q)
|
88% |
24911
193.9 IPS |
|
|
Style Transfer (SP)
|
100% |
19961
25.7 IPS |
|
|
Style Transfer (HP)
|
100% |
20364
26.2 IPS |
|
|
Style Transfer (Q)
|
98% |
76573
98.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4273
157.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4387
162.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
15371
569.2 IPS |
|
|
Text Classification (SP)
|
100% |
3635
4.85 KIPS |
|
|
Text Classification (HP)
|
100% |
3687
4.92 KIPS |
|
|
Text Classification (Q)
|
92% |
5596
7.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
5142
88.6 IPS |
|
|
Machine Translation (HP)
|
100% |
5082
87.5 IPS |
|
|
Machine Translation (Q)
|
100% |
6865
118.2 IPS |
