Mac mini (2023)
Geekbench AI Score
4144
Single Precision Score
6756
Half Precision Score
5307
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| User | gbjdsv |
| Upload Date | November 15 2024 10:50 PM |
| Views | 3 |
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, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.47 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1391
258.6 IPS |
|
|
Image Classification (HP)
|
100% |
2263
420.9 IPS |
|
|
Image Classification (Q)
|
96% |
1656
309.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1711
27.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2496
40.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
2931
47.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
12645
14.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
25007
29.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
19443
22.8 IPS |
|
|
Object Detection (SP)
|
100% |
1690
134.1 IPS |
|
|
Object Detection (HP)
|
97% |
2726
217.0 IPS |
|
|
Object Detection (Q)
|
94% |
1968
156.9 IPS |
|
|
Face Detection (SP)
|
100% |
3537
42.0 IPS |
|
|
Face Detection (HP)
|
100% |
6017
71.5 IPS |
|
|
Face Detection (Q)
|
100% |
3409
40.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6379
49.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
12199
94.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
8292
64.8 IPS |
|
|
Style Transfer (SP)
|
100% |
25242
32.4 IPS |
|
|
Style Transfer (HP)
|
100% |
39634
51.0 IPS |
|
|
Style Transfer (Q)
|
96% |
30443
39.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5140
189.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7064
260.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4439
163.9 IPS |
|
|
Text Classification (SP)
|
100% |
2338
3.12 KIPS |
|
|
Text Classification (HP)
|
100% |
3988
5.32 KIPS |
|
|
Text Classification (Q)
|
93% |
3971
5.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
4291
73.9 IPS |
|
|
Machine Translation (HP)
|
98% |
6285
108.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6301
108.9 IPS |
