Mac Studio M2 Max Mac Studio (2023)
Geekbench AI Score
4116
Single Precision Score
26905
Half Precision Score
30041
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | enroscado |
| Upload Date | April 29 2025 02:26 AM |
| Views | 19 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.4.1 (Build 24E263) |
| 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 | 3.68 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1392
258.9 IPS |
|
|
Image Classification (HP)
|
100% |
13507
2.51 KIPS |
|
|
Image Classification (Q)
|
96% |
16166
3.02 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1632
26.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
19937
323.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
24302
393.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
12908
15.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
105487
123.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
104361
122.3 IPS |
|
|
Object Detection (SP)
|
100% |
1675
132.9 IPS |
|
|
Object Detection (HP)
|
99% |
15552
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
17411
1.39 KIPS |
|
|
Face Detection (SP)
|
100% |
3462
41.1 IPS |
|
|
Face Detection (HP)
|
100% |
35642
423.5 IPS |
|
|
Face Detection (Q)
|
100% |
46178
548.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6198
47.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
87439
673.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
107477
839.9 IPS |
|
|
Style Transfer (SP)
|
100% |
25229
32.4 IPS |
|
|
Style Transfer (HP)
|
100% |
203446
261.5 IPS |
|
|
Style Transfer (Q)
|
96% |
189801
244.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4999
184.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
40981
1.51 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
49285
1.82 KIPS |
|
|
Text Classification (SP)
|
100% |
2376
3.17 KIPS |
|
|
Text Classification (HP)
|
100% |
4079
5.44 KIPS |
|
|
Text Classification (Q)
|
93% |
4060
5.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
4429
76.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4246
73.1 IPS |
|
|
Machine Translation (Q)
|
98% |
4449
76.9 IPS |
