Framework Laptop 16 (AMD Ryzen 7040 Series)
Geekbench AI Score
3306
Single Precision Score
834
Half Precision Score
7199
Quantized Score
Geekbench AI 1.6.0 for Linux AVX2
Result Information
| User | jooe |
| Upload Date | February 01 2026 09:49 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 7 7840HS |
| System Information | |
|---|---|
| Operating System | Fedora Linux 43 (Workstation Edition) |
| Model | Framework Laptop 16 (AMD Ryzen 7040 Series) |
| Motherboard | Framework FRANMZCP07 |
| 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 |
| Memory Information | |
|---|---|
| Size | 30.65 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2286
425.2 IPS |
|
|
Image Classification (HP)
|
100% |
157
29.1 IPS |
|
|
Image Classification (Q)
|
97% |
7715
1.44 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1466
23.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
310
5.03 IPS |
|
|
Image Segmentation (Q)
|
99% |
3625
58.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6649
7.76 IPS |
|
|
Pose Estimation (HP)
|
100% |
5078
5.93 IPS |
|
|
Pose Estimation (Q)
|
94% |
25037
29.4 IPS |
|
|
Object Detection (SP)
|
100% |
2459
195.1 IPS |
|
|
Object Detection (HP)
|
100% |
274
21.7 IPS |
|
|
Object Detection (Q)
|
86% |
7703
619.1 IPS |
|
|
Face Detection (SP)
|
100% |
3714
44.1 IPS |
|
|
Face Detection (HP)
|
100% |
464
5.51 IPS |
|
|
Face Detection (Q)
|
97% |
17410
207.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7406
57.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
965
7.43 IPS |
|
|
Depth Estimation (Q)
|
78% |
9368
74.8 IPS |
|
|
Style Transfer (SP)
|
100% |
10030
12.9 IPS |
|
|
Style Transfer (HP)
|
100% |
8804
11.3 IPS |
|
|
Style Transfer (Q)
|
98% |
21626
27.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2659
98.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2133
78.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3415
126.4 IPS |
|
|
Text Classification (SP)
|
100% |
1867
2.49 KIPS |
|
|
Text Classification (HP)
|
100% |
576
769.1 IPS |
|
|
Text Classification (Q)
|
97% |
1757
2.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
2083
35.9 IPS |
|
|
Machine Translation (HP)
|
100% |
498
8.59 IPS |
|
|
Machine Translation (Q)
|
65% |
3279
65.9 IPS |
