Mac mini (2023)
Geekbench AI Score
4316
Single Precision Score
7010
Half Precision Score
5474
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | November 17 2024 06:54 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.43 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1461
271.8 IPS |
|
|
Image Classification (HP)
|
100% |
2383
443.2 IPS |
|
|
Image Classification (Q)
|
96% |
1710
319.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1798
29.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2614
42.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
3029
49.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
13009
15.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
25274
29.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
19780
23.2 IPS |
|
|
Object Detection (SP)
|
100% |
1784
141.5 IPS |
|
|
Object Detection (HP)
|
97% |
2912
231.8 IPS |
|
|
Object Detection (Q)
|
94% |
2067
164.7 IPS |
|
|
Face Detection (SP)
|
100% |
3752
44.6 IPS |
|
|
Face Detection (HP)
|
100% |
6246
74.2 IPS |
|
|
Face Detection (Q)
|
100% |
3502
41.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6419
49.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
12543
97.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
8355
65.3 IPS |
|
|
Style Transfer (SP)
|
100% |
26316
33.8 IPS |
|
|
Style Transfer (HP)
|
100% |
41028
52.7 IPS |
|
|
Style Transfer (Q)
|
96% |
31632
40.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5362
198.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7261
268.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4636
171.2 IPS |
|
|
Text Classification (SP)
|
100% |
2290
3.06 KIPS |
|
|
Text Classification (HP)
|
100% |
4009
5.35 KIPS |
|
|
Text Classification (Q)
|
93% |
4001
5.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
4738
81.6 IPS |
|
|
Machine Translation (HP)
|
98% |
6684
115.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6652
115.0 IPS |
