Framework Laptop
Geekbench AI Score
2445
Single Precision Score
2524
Half Precision Score
1547
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | WillerZ |
| Upload Date | December 30 2025 10:28 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Iris(R) Xe Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Framework Laptop |
| Motherboard | Framework FRANBMCP03 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i5-1135G7 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 140 Stepping 1 |
| Base Frequency | 2.42 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1078
200.5 IPS |
|
|
Image Classification (HP)
|
100% |
1108
206.1 IPS |
|
|
Image Classification (Q)
|
100% |
908
168.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1512
24.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1803
29.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1103
17.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8517
9.94 IPS |
|
|
Pose Estimation (HP)
|
100% |
9926
11.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
4767
5.58 IPS |
|
|
Object Detection (SP)
|
100% |
1247
98.9 IPS |
|
|
Object Detection (HP)
|
98% |
1082
86.1 IPS |
|
|
Object Detection (Q)
|
86% |
1029
82.7 IPS |
|
|
Face Detection (SP)
|
100% |
2245
26.7 IPS |
|
|
Face Detection (HP)
|
100% |
2835
33.7 IPS |
|
|
Face Detection (Q)
|
97% |
1646
19.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
4805
37.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
5440
42.0 IPS |
|
|
Depth Estimation (Q)
|
77% |
3346
26.8 IPS |
|
|
Style Transfer (SP)
|
100% |
19560
25.1 IPS |
|
|
Style Transfer (HP)
|
100% |
25618
32.9 IPS |
|
|
Style Transfer (Q)
|
98% |
12307
15.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3092
114.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3831
141.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1256
46.5 IPS |
|
|
Text Classification (SP)
|
100% |
755
1.01 KIPS |
|
|
Text Classification (HP)
|
100% |
388
518.2 IPS |
|
|
Text Classification (Q)
|
97% |
426
570.6 IPS |
|
|
Machine Translation (SP)
|
100% |
898
15.5 IPS |
|
|
Machine Translation (HP)
|
100% |
833
14.4 IPS |
|
|
Machine Translation (Q)
|
70% |
441
8.27 IPS |
