Mac Studio
Geekbench AI Score
1991
Single Precision Score
12714
Half Precision Score
12967
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| User | sfoskett |
| Upload Date | August 15 2024 07:21 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M1 Max |
| System Information | |
|---|---|
| Operating System | macOS 14.5 (Build 23F79) |
| Model | Mac Studio |
| Model ID | Mac13,1 |
| Motherboard | Mac13,1 |
| CPU Information | |
|---|---|
| Name | Apple M1 Max |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M1 Max |
| Base Frequency | 3.22 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
900
167.4 IPS |
|
|
Image Classification (HP)
|
100% |
7143
1.33 KIPS |
|
|
Image Classification (Q)
|
99% |
7419
1.38 KIPS |
|
|
Image Segmentation (SP)
|
100% |
672
10.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
3878
62.9 IPS |
|
|
Image Segmentation (Q)
|
100% |
3879
62.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
10144
11.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
69442
81.0 IPS |
|
|
Pose Estimation (Q)
|
94% |
64705
75.9 IPS |
|
|
Object Detection (SP)
|
100% |
1090
86.5 IPS |
|
|
Object Detection (HP)
|
99% |
7582
603.1 IPS |
|
|
Object Detection (Q)
|
93% |
7235
577.3 IPS |
|
|
Face Detection (SP)
|
100% |
1954
23.2 IPS |
|
|
Face Detection (HP)
|
100% |
11383
135.3 IPS |
|
|
Face Detection (Q)
|
100% |
11228
133.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
3499
27.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
46091
355.1 IPS |
|
|
Depth Estimation (Q)
|
97% |
49708
384.3 IPS |
|
|
Style Transfer (SP)
|
100% |
12225
15.7 IPS |
|
|
Style Transfer (HP)
|
100% |
117952
151.6 IPS |
|
|
Style Transfer (Q)
|
100% |
122783
157.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2422
89.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18717
691.1 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
22954
850.4 IPS |
|
|
Text Classification (SP)
|
100% |
449
598.9 IPS |
|
|
Text Classification (HP)
|
100% |
3407
4.55 KIPS |
|
|
Text Classification (Q)
|
93% |
3299
4.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
1611
27.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1918
33.0 IPS |
|
|
Machine Translation (Q)
|
98% |
1923
33.2 IPS |
