Apple Inc. iMac13,2
Geekbench AI Score
24
Single Precision Score
24
Half Precision Score
18
Quantized Score
Geekbench AI 1.1.0 for Linux x86 (64-bit)
Result Information
| Upload Date | November 17 2024 04:48 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i7-3770 |
| System Information | |
|---|---|
| Operating System | Linux Mint 22 |
| Model | Apple Inc. iMac13,2 |
| Motherboard | Apple Inc. Mac-FC02E91DDD3FA6A4 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-3770 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 58 Stepping 9 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 31.28 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
15
2.85 IPS |
|
|
Image Classification (HP)
|
100% |
15
2.86 IPS |
|
|
Image Classification (Q)
|
97% |
12
2.20 IPS |
|
|
Image Segmentation (SP)
|
100% |
21
0.33 IPS |
|
|
Image Segmentation (HP)
|
100% |
21
0.34 IPS |
|
|
Image Segmentation (Q)
|
98% |
16
0.26 IPS |
|
|
Pose Estimation (SP)
|
100% |
20
0.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
20
0.02 IPS |
|
|
Pose Estimation (Q)
|
96% |
16
0.02 IPS |
|
|
Object Detection (SP)
|
100% |
13
1.05 IPS |
|
|
Object Detection (HP)
|
100% |
13
1.07 IPS |
|
|
Object Detection (Q)
|
87% |
10
0.83 IPS |
|
|
Face Detection (SP)
|
100% |
51
0.61 IPS |
|
|
Face Detection (HP)
|
100% |
51
0.61 IPS |
|
|
Face Detection (Q)
|
97% |
36
0.44 IPS |
|
|
Depth Estimation (SP)
|
100% |
31
0.24 IPS |
|
|
Depth Estimation (HP)
|
99% |
32
0.24 IPS |
|
|
Depth Estimation (Q)
|
64% |
21
0.19 IPS |
|
|
Style Transfer (SP)
|
100% |
65
0.08 IPS |
|
|
Style Transfer (HP)
|
100% |
65
0.08 IPS |
|
|
Style Transfer (Q)
|
98% |
53
0.07 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
14
0.53 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14
0.52 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
11
0.41 IPS |
|
|
Text Classification (SP)
|
100% |
21
27.8 IPS |
|
|
Text Classification (HP)
|
100% |
21
27.8 IPS |
|
|
Text Classification (Q)
|
91% |
15
20.7 IPS |
|
|
Machine Translation (SP)
|
100% |
36
0.62 IPS |
|
|
Machine Translation (HP)
|
100% |
35
0.60 IPS |
|
|
Machine Translation (Q)
|
58% |
18
0.44 IPS |
