Mac Studio (2023)
Geekbench AI Score
3222
Single Precision Score
4819
Half Precision Score
4166
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| User | VenomF5 |
| Upload Date | September 25 2024 11:07 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| 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% |
1487
276.5 IPS |
|
|
Image Classification (HP)
|
100% |
1829
340.2 IPS |
|
|
Image Classification (Q)
|
96% |
1426
266.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1322
21.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1307
21.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
1859
30.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6387
7.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
14932
17.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
12866
15.1 IPS |
|
|
Object Detection (SP)
|
100% |
1618
128.3 IPS |
|
|
Object Detection (HP)
|
97% |
2254
179.4 IPS |
|
|
Object Detection (Q)
|
94% |
1731
138.0 IPS |
|
|
Face Detection (SP)
|
100% |
3032
36.0 IPS |
|
|
Face Detection (HP)
|
100% |
4462
53.0 IPS |
|
|
Face Detection (Q)
|
100% |
2942
35.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5602
43.2 IPS |
|
|
Depth Estimation (HP)
|
97% |
8669
67.0 IPS |
|
|
Depth Estimation (Q)
|
86% |
6561
51.2 IPS |
|
|
Style Transfer (SP)
|
100% |
16957
21.8 IPS |
|
|
Style Transfer (HP)
|
100% |
26980
34.7 IPS |
|
|
Style Transfer (Q)
|
96% |
22500
29.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3826
141.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4861
179.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3652
134.9 IPS |
|
|
Text Classification (SP)
|
100% |
2303
3.07 KIPS |
|
|
Text Classification (HP)
|
100% |
3640
4.86 KIPS |
|
|
Text Classification (Q)
|
93% |
3682
4.94 KIPS |
|
|
Machine Translation (SP)
|
100% |
2343
40.4 IPS |
|
|
Machine Translation (HP)
|
98% |
4550
78.6 IPS |
|
|
Machine Translation (Q)
|
98% |
4570
79.0 IPS |
