Acemagic Matrix Mini M1 Default string Default string
Geekbench AI Score
4355
Single Precision Score
6251
Half Precision Score
9549
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | Spektr48K |
| Upload Date | November 19 2025 06:55 PM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Iris(R) Xe Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Default string Default string |
| Motherboard | Default string Default string |
| Power Plan | Equilibrado |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13900HK |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2879
535.4 IPS |
|
|
Image Classification (HP)
|
100% |
4454
828.2 IPS |
|
|
Image Classification (Q)
|
99% |
5590
1.04 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3860
62.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
6394
103.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
7364
119.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
9852
11.5 IPS |
|
|
Pose Estimation (HP)
|
99% |
7294
8.51 IPS |
|
|
Pose Estimation (Q)
|
97% |
30091
35.2 IPS |
|
|
Object Detection (SP)
|
100% |
2647
210.0 IPS |
|
|
Object Detection (HP)
|
100% |
3807
301.9 IPS |
|
|
Object Detection (Q)
|
90% |
6673
533.6 IPS |
|
|
Face Detection (SP)
|
100% |
5383
64.0 IPS |
|
|
Face Detection (HP)
|
100% |
10078
119.7 IPS |
|
|
Face Detection (Q)
|
100% |
15406
183.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
9300
71.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
14679
113.5 IPS |
|
|
Depth Estimation (Q)
|
89% |
19506
151.7 IPS |
|
|
Style Transfer (SP)
|
100% |
25115
32.3 IPS |
|
|
Style Transfer (HP)
|
100% |
34384
44.2 IPS |
|
|
Style Transfer (Q)
|
98% |
67880
87.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4233
156.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6590
243.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
12228
452.9 IPS |
|
|
Text Classification (SP)
|
71% |
1181
1.71 KIPS |
|
|
Text Classification (HP)
|
71% |
1374
1.99 KIPS |
|
|
Text Classification (Q)
|
92% |
1356
1.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
1349
23.2 IPS |
|
|
Machine Translation (HP)
|
98% |
2504
43.3 IPS |
|
|
Machine Translation (Q)
|
98% |
2256
39.0 IPS |
