Framework Laptop 16 (AMD Ryzen 7040 Series)
Geekbench ML Score
9361
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | January 25 2024 07:12 AM |
| Views | 11 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (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 |
| 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | AMD Radeon(TM) RX 7700S |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5357
1.00 KIPS |
|
|
Image Classification (F16)
|
100% |
4991
934.0 IPS |
|
|
Image Classification (I8)
|
100% |
4679
875.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
6935
115.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
6238
104.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
6283
104.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
67972
82.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
93541
113.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
53957
65.3 IPS |
|
|
Object Detection (F32)
|
100% |
2321
173.3 IPS |
|
|
Object Detection (F16)
|
100% |
2346
175.2 IPS |
|
|
Object Detection (I8)
|
62% |
2266
169.2 IPS |
|
|
Face Detection (F32)
|
100% |
12018
142.9 IPS |
|
|
Face Detection (F16)
|
100% |
14320
170.3 IPS |
|
|
Face Detection (I8)
|
89% |
10654
126.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
26626
206.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
26481
205.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
27391
212.4 IPS |
|
|
Style Transfer (F32)
|
100% |
112100
147.5 IPS |
|
|
Style Transfer (F16)
|
100% |
110798
145.7 IPS |
|
|
Style Transfer (I8)
|
98% |
101683
133.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9816
350.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10049
358.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
11712
418.3 IPS |
|
|
Text Classification (F32)
|
100% |
1468
2.11 KIPS |
|
|
Text Classification (F16)
|
100% |
1502
2.16 KIPS |
|
|
Text Classification (I8)
|
98% |
1233
1.77 KIPS |
|
|
Machine Translation (F32)
|
100% |
2159
39.7 IPS |
|
|
Machine Translation (F16)
|
100% |
2337
43.0 IPS |
|
|
Machine Translation (I8)
|
70% |
1355
24.9 IPS |
