Mac Studio (2023)
Geekbench AI Score
4119
Single Precision Score
6625
Half Precision Score
5288
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | danilonc |
| Upload Date | June 27 2025 07:28 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F74) |
| Model | Mac Studio (2023) |
| Model ID | Mac14,13 |
| Motherboard | Mac14,13 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1388
258.2 IPS |
|
|
Image Classification (HP)
|
100% |
2235
415.6 IPS |
|
|
Image Classification (Q)
|
96% |
1652
308.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1668
27.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2463
39.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
2885
46.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
12934
15.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
25606
29.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
19623
23.0 IPS |
|
|
Object Detection (SP)
|
100% |
1665
132.1 IPS |
|
|
Object Detection (HP)
|
97% |
2636
209.9 IPS |
|
|
Object Detection (Q)
|
94% |
1977
157.6 IPS |
|
|
Face Detection (SP)
|
100% |
3455
41.1 IPS |
|
|
Face Detection (HP)
|
100% |
5517
65.6 IPS |
|
|
Face Detection (Q)
|
100% |
3357
39.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6165
47.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
11223
86.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
7750
60.6 IPS |
|
|
Style Transfer (SP)
|
100% |
25007
32.1 IPS |
|
|
Style Transfer (HP)
|
100% |
38555
49.6 IPS |
|
|
Style Transfer (Q)
|
96% |
29476
38.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5070
187.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6448
238.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4502
166.2 IPS |
|
|
Text Classification (SP)
|
100% |
2378
3.17 KIPS |
|
|
Text Classification (HP)
|
100% |
4204
5.61 KIPS |
|
|
Text Classification (Q)
|
93% |
4136
5.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
4393
75.7 IPS |
|
|
Machine Translation (HP)
|
98% |
6781
117.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6481
112.0 IPS |
