Mac Studio (2023)
Geekbench AI Score
3921
Single Precision Score
6840
Half Precision Score
5404
Quantized Score
Geekbench AI 1.7.0 for macOS AArch64
Result Information
| User | alexeft |
| Upload Date | March 16 2026 06:03 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 26.3.1 (Build 25D2128) |
| 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 | 3.44 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1297
241.2 IPS |
|
|
Image Classification (HP)
|
100% |
2248
418.0 IPS |
|
|
Image Classification (Q)
|
96% |
1672
312.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1639
26.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2536
41.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
2905
47.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
10912
12.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
26309
30.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
20158
23.6 IPS |
|
|
Object Detection (SP)
|
100% |
1525
121.0 IPS |
|
|
Object Detection (HP)
|
97% |
2745
218.5 IPS |
|
|
Object Detection (Q)
|
94% |
2002
159.6 IPS |
|
|
Face Detection (SP)
|
100% |
3473
41.3 IPS |
|
|
Face Detection (HP)
|
100% |
5892
70.0 IPS |
|
|
Face Detection (Q)
|
100% |
3348
39.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5756
44.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
11332
87.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
8106
63.4 IPS |
|
|
Style Transfer (SP)
|
100% |
25226
32.4 IPS |
|
|
Style Transfer (HP)
|
100% |
40970
52.7 IPS |
|
|
Style Transfer (Q)
|
96% |
32297
41.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4745
175.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6545
241.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4426
163.4 IPS |
|
|
Text Classification (SP)
|
100% |
2415
3.22 KIPS |
|
|
Text Classification (HP)
|
99% |
4206
5.61 KIPS |
|
|
Text Classification (Q)
|
93% |
4106
5.51 KIPS |
|
|
Machine Translation (SP)
|
100% |
4211
72.5 IPS |
|
|
Machine Translation (HP)
|
98% |
7237
125.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6808
117.7 IPS |
