TOSHIBA PORTEGE Z30-A
Geekbench AI Score
881
Single Precision Score
863
Half Precision Score
941
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | July 23 2025 08:16 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i5-4310U CPU @ 2.00GHz |
| System Information | |
|---|---|
| Operating System | Windows 10 Pro (64-bit) |
| Model | TOSHIBA PORTEGE Z30-A |
| Motherboard | TOSHIBA PORTEGE Z30-A |
| CPU Information | |
|---|---|
| Name | Intel Core i5-4310U |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 69 Stepping 1 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
494
91.9 IPS |
|
|
Image Classification (HP)
|
100% |
488
90.7 IPS |
|
|
Image Classification (Q)
|
100% |
548
102.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
562
9.11 IPS |
|
|
Image Segmentation (HP)
|
100% |
563
9.13 IPS |
|
|
Image Segmentation (Q)
|
99% |
630
10.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1015
1.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
932
1.09 IPS |
|
|
Pose Estimation (Q)
|
94% |
1163
1.36 IPS |
|
|
Object Detection (SP)
|
100% |
486
38.6 IPS |
|
|
Object Detection (HP)
|
100% |
483
38.3 IPS |
|
|
Object Detection (Q)
|
87% |
562
45.1 IPS |
|
|
Face Detection (SP)
|
100% |
1269
15.1 IPS |
|
|
Face Detection (HP)
|
100% |
1286
15.3 IPS |
|
|
Face Detection (Q)
|
97% |
1551
18.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1309
10.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1130
8.71 IPS |
|
|
Depth Estimation (Q)
|
81% |
1474
11.6 IPS |
|
|
Style Transfer (SP)
|
100% |
3038
3.91 IPS |
|
|
Style Transfer (HP)
|
100% |
3013
3.87 IPS |
|
|
Style Transfer (Q)
|
98% |
3344
4.31 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
622
23.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
624
23.1 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
704
26.1 IPS |
|
|
Text Classification (SP)
|
100% |
685
914.4 IPS |
|
|
Text Classification (HP)
|
100% |
695
928.2 IPS |
|
|
Text Classification (Q)
|
91% |
479
643.3 IPS |
|
|
Machine Translation (SP)
|
100% |
960
16.5 IPS |
|
|
Machine Translation (HP)
|
100% |
983
16.9 IPS |
|
|
Machine Translation (Q)
|
100% |
938
16.2 IPS |
