Mac mini (2023)
Geekbench AI Score
10655
Single Precision Score
11817
Half Precision Score
10463
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | November 17 2024 06:49 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| 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 | 3.48 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5599
1.04 KIPS |
|
|
Image Classification (HP)
|
100% |
5871
1.09 KIPS |
|
|
Image Classification (Q)
|
97% |
4899
914.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
8312
134.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
8428
136.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
8216
133.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
45322
52.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
48109
56.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
44745
52.4 IPS |
|
|
Object Detection (SP)
|
100% |
4822
382.5 IPS |
|
|
Object Detection (HP)
|
100% |
5410
429.1 IPS |
|
|
Object Detection (Q)
|
91% |
4523
361.4 IPS |
|
|
Face Detection (SP)
|
100% |
18504
219.9 IPS |
|
|
Face Detection (HP)
|
100% |
20244
240.5 IPS |
|
|
Face Detection (Q)
|
100% |
14123
167.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
26916
207.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
27901
215.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
23117
180.7 IPS |
|
|
Style Transfer (SP)
|
100% |
80819
103.9 IPS |
|
|
Style Transfer (HP)
|
100% |
86957
111.8 IPS |
|
|
Style Transfer (Q)
|
96% |
81080
104.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
18357
677.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
19384
715.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
15664
578.4 IPS |
|
|
Text Classification (SP)
|
100% |
2293
3.06 KIPS |
|
|
Text Classification (HP)
|
100% |
4022
5.37 KIPS |
|
|
Text Classification (Q)
|
93% |
4024
5.40 KIPS |
|
|
Machine Translation (SP)
|
100% |
1095
18.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1077
18.5 IPS |
|
|
Machine Translation (Q)
|
98% |
1157
20.0 IPS |
