Framework Laptop 16 (AMD Ryzen 7040 Series)
Geekbench AI Score
86
Single Precision Score
86
Half Precision Score
58
Quantized Score
Geekbench AI 1.5.0 for Linux x86 (64-bit)
Result Information
| User | foobar23 |
| Upload Date | October 14 2025 02:21 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Ryzen 7 7840HS |
| System Information | |
|---|---|
| Operating System | Fedora Linux 42 (KDE Plasma Desktop 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 | 86.22 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
52
9.58 IPS |
|
|
Image Classification (HP)
|
100% |
51
9.57 IPS |
|
|
Image Classification (Q)
|
97% |
37
6.89 IPS |
|
|
Image Segmentation (SP)
|
100% |
70
1.14 IPS |
|
|
Image Segmentation (HP)
|
100% |
70
1.14 IPS |
|
|
Image Segmentation (Q)
|
98% |
48
0.79 IPS |
|
|
Pose Estimation (SP)
|
100% |
82
0.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
81
0.09 IPS |
|
|
Pose Estimation (Q)
|
96% |
59
0.07 IPS |
|
|
Object Detection (SP)
|
100% |
45
3.60 IPS |
|
|
Object Detection (HP)
|
100% |
45
3.58 IPS |
|
|
Object Detection (Q)
|
87% |
32
2.57 IPS |
|
|
Face Detection (SP)
|
100% |
149
1.78 IPS |
|
|
Face Detection (HP)
|
100% |
146
1.74 IPS |
|
|
Face Detection (Q)
|
97% |
109
1.30 IPS |
|
|
Depth Estimation (SP)
|
100% |
113
0.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
114
0.87 IPS |
|
|
Depth Estimation (Q)
|
64% |
70
0.64 IPS |
|
|
Style Transfer (SP)
|
100% |
246
0.32 IPS |
|
|
Style Transfer (HP)
|
100% |
249
0.32 IPS |
|
|
Style Transfer (Q)
|
98% |
180
0.23 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
53
1.95 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
53
1.95 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
38
1.40 IPS |
|
|
Text Classification (SP)
|
100% |
64
85.5 IPS |
|
|
Text Classification (HP)
|
100% |
66
87.9 IPS |
|
|
Text Classification (Q)
|
91% |
45
60.9 IPS |
|
|
Machine Translation (SP)
|
100% |
121
2.08 IPS |
|
|
Machine Translation (HP)
|
100% |
122
2.10 IPS |
|
|
Machine Translation (Q)
|
58% |
56
1.35 IPS |
