Micro-Star International Co., Ltd. MS-7E27
Geekbench AI Score
2574
Single Precision Score
2599
Half Precision Score
1575
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| Upload Date | December 27 2024 09:56 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD Ryzen 5 7500F |
| System Information | |
|---|---|
| Operating System | Ubuntu 24.10 |
| Model | Micro-Star International Co., Ltd. MS-7E27 |
| Motherboard | Micro-Star International Co., Ltd. PRO B650M-P (MS-7E27) |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 7500F |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 25 Model 97 Stepping 2 |
| Base Frequency | 5.20 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 30.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1593
296.2 IPS |
|
|
Image Classification (HP)
|
100% |
1695
315.3 IPS |
|
|
Image Classification (Q)
|
99% |
961
179.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2472
40.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2499
40.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1052
17.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2826
3.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
2808
3.28 IPS |
|
|
Pose Estimation (Q)
|
96% |
3101
3.63 IPS |
|
|
Object Detection (SP)
|
100% |
1603
127.1 IPS |
|
|
Object Detection (HP)
|
100% |
1570
124.5 IPS |
|
|
Object Detection (Q)
|
85% |
1085
87.3 IPS |
|
|
Face Detection (SP)
|
100% |
3732
44.3 IPS |
|
|
Face Detection (HP)
|
100% |
3757
44.6 IPS |
|
|
Face Detection (Q)
|
97% |
2486
29.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
3056
23.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
3046
23.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
1890
17.7 IPS |
|
|
Style Transfer (SP)
|
100% |
3724
4.79 IPS |
|
|
Style Transfer (HP)
|
100% |
3748
4.82 IPS |
|
|
Style Transfer (Q)
|
98% |
5734
7.39 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2142
79.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2168
80.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1665
61.7 IPS |
|
|
Text Classification (SP)
|
100% |
2474
3.30 KIPS |
|
|
Text Classification (HP)
|
100% |
2490
3.32 KIPS |
|
|
Text Classification (Q)
|
92% |
852
1.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
3186
54.9 IPS |
|
|
Machine Translation (HP)
|
100% |
3258
56.1 IPS |
|
|
Machine Translation (Q)
|
58% |
724
17.0 IPS |
